bluuebunny/crossref_metadata_2025 huggingface dataset:
Historical Development of Urban Green Infrastructure and Possibilities of its Implementation in the Republic of Croatia
Authors: Hrdalo Ines , Pereković Petra , Tomić Reljić Dora
Published: July 2021

Research has been motivated by a wide range of concepts of the term urban green infrastructure. As the aim was to indicate a clear basis for the term, an investigation of its development was a necessity, not only in the European, but also in a broader context. Although green infrastructure is included in the 21st century policies of protection and development of EU landscapes, its foundations can be traced back to the models of ideal Renaissance towns and urbanist concepts mainly from the 19th and 20th century. In these historical periods used concepts meant urban landscapes as systems, a part of the environment, as seen in green corridors, green belts, green wedges, green networks and through the perception of urban green systems. As a modern concept the urban green infrastructure has been upgraded with developed roles, extending functions, scopes and scales from previous historical models. In that sense it maintains its social role of improving the quality of life in towns, while at the same time defining town texture with its urban morphological significance. At the same time it also develops ecological values and extends its scale to nonurban local, regional and international contexts.
Despite its benefits, spatial planning documents in the Republic of Croatia still lack measures and actions which would recognise the true benefit of green infrastructure in spatial development.
Relative Fat Mass, a new tool for measuring obesity, could predict the complications of type 2 diabetes
Authors: Jambart Isabelle
Published: July 2021

Aim/background: Obesity is a chronic disease contributing to many metabolic illnesses, in particular type 2 diabetes. The Relative Fat Mass (RFM) is a tool recently introduced for obesity which better predicts the level of visceral fat than the Body Mass Index (BMI). The aim of this study is to determine whether RFM is a better predictor of the cardiometabolic risk factors and the complications of type 2 diabetes than BMI. Materials and methods: This is a cross sectional study. A list of information was collected from endocrinologists treating type 2 diabetic patients in a primary healthcare clinic and a tertiary hospital in Beirut. This list allowed us to evaluate the micro and macro vascular complications of type 2 diabetic patients, to assess their risk factors and to calculate their RFM and BMI. Results: We analyzed the data of 359 patients. Higher RFM was associated with higher systolic blood pressure (p < 0.05), and both RFM and BMI were significantly correlated to higher CRP, triglyceride levels and liver enzymes. However, the BMI was better associated with other cardiometabolic risk factors such as the total cholesterol (p = 0,003), LDL cholesterol (p = 0,002) and HbA1c (p = 0,01) than RFM. Both RFM and BMI were correlated with higher microalbuminuria (p < 0.001) but unlike BMI, higher RFM was associated with higher creatinine level (p = 0.317 versus 0.047 respectively) and therefore better linked to diabetic nephropathy than BMI. More importantly, we observed an unprecedented result, associating RFM to diabetic neuropathy: a normal RFM excludes diabetic neuropathy with a high probability of 82.5%. Furthermore, a RFM cutoff value of 30.76 in men and 43.31 in women showed an increased risk of developing diabetic neuropathy by 2.464. No association was observed between RFM and diabetic retinopathy. Conclusion: The RFM better predicts microvascular complications of diabetes than BMI except for retinopathy. It is also associated with a worse profile of metabolic syndrome. This study is unique in its discovery of the potential role of RFM as a tool which could rule out neuropathy in diabetic patients.
Corporate Social Responsibility PT. Semen Tonasa dalam Penanganan Fakir Miskin di Wilayah Pesisir Desa Bulu Cindea Kabupaten Pangkep Sulawesi Selatan
Authors: Parawangsa Rachmat , Lestari Indra
Published: July 2021

This study discusses the implementation of empowerment of poor women’s business groups thought PT Semen Tonasa’s Corporate Social Responsibility (CSR) in the coastal area of Bulu Cindea Village, Pangkep Regency. The research was conducted with the aim of describing and improving information broadly and in dept( qualtitative descriptive) on the Onasa Mandiri Program in the form of training and procurement of womend’s business groips. The research results provide a specific detailed description including; poverty condition, realization of the CSR fund budget, The TOnasa Mandiri Program, Impelmentation of community empowerment programs, as wel as obstacles to community empowerment
Strategi Koping Pada Anak yang Memiliki Pengalaman Kehilangan Orang Tua di LKSA Nugraha Kota Bandung
Authors: Pratama Denny Maulana
Published: July 2021

Tujuan penelitian ini adalah untuk mendeskripsikan dan menganalisis karakteristik anak, latar belakang kehilangan orang tua yang dialami anak, strategi berpusat pada masalah serta strategi berpusat pada emosi pada anak. Penelitian ini menggunakan metode kualitatif dengan pendekatan deskriptif. Informan dalam penelitian ini meliputi 6 orang anak dan 2 orang pengasuh. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah wawancara mendalam dan studi dokumentasi. Pemeriksaan keabsahan data juga dilakukan melalui triangulasi sumber dan waktu. Teknik analisis data dilakukan dengan cara reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan strategi koping yang dilakukan anak sudah tergolong baik karena melakukan dua jenis koping yakni strategi berpusat pada masalah dan strategi berpusat pada emosi, namun masih terdapat permasalahan pada strategi berpusat pada masalah yakni anak belum memiliki inisiatif dalam mengungkapkan permasalahan kepada pengasuh dan belum tersedianya media pertemuan kelompok dalam pengungkapan permasalahan kehilangan orang tua. Selain itu terdapat juga permasalahan dalam strategi berpusat pada emosi yakni anak memilih tidak mengungkapkan emosi yang dirasakannya,  masih adanya penolakan atas kehilangan orang tua, serta perasaaan rendah diri yang masih dimiliki oleh anak yang memiliki pengalaman kehilangan orang tua. Berdasarkan permasalahan tersebut, peneliti merumuskan program pemberdayaan kelompok bagi anak yang memiliki pengalaman kehilangan orang tua.
Efektivitas Pusat Kesejahteraan Sosial “As Salam” Desa Katapang Kecamatan Katapang Kabupaten Bandung
Authors: Sukoco Dwi Heru
Published: July 2021

Pusat Kesejahteraan Sosial (Puskesos) “As Salaam” merupakan lembaga layanan dan rujukan terpadu tingkat desa untuk memberikan kemudahan keluarga miskin mengakses dan menjangkau program Perlindungan Sosial dan Penanggulangan Kemiskinan (PSPK). Penelitian menggunakan pendekatan kualitatif dengan informan manajer, fasilitator, kepala desa, pengurus, dan penerima manfaat. Teknik pengumpulan datanya triangulasi, memadukan wawancara, observasi, dan studi dokumentasi. Uji keabsahan data menggunakan teknik credibility, transferability, dependability, and confirmability. Teknik analisis data menggunakan Model Mile & Huberman. Hasil penelitian menunjukkan Puskesos “As Salaam” merupakan puskesos baru, namun mampu mencapai tujuannya. Puskesos “As Salaam” mampu: (1) menjadi pusat informasi dan data; (2) melayani, menangani, dan menyelesaikan keluhan keluarga miskin; (3) merujuk keluhan ke layanan lebih tinggi; dan (4) memfasilitasi pemuktahiran Data Terpadu Kesejahteraan Sosial (DTKS). Puskesos “As Salaam” memiliki prestasi: mendapat penghargaan sebagai Puskesos terbaik se Kabupaten Bandung, kunjungan tamu dari dalam dan luar negeri, tempat studi banding, lokasi penelitian dan praktik lapangan mahasiswa. Jadi Puskesos “As Salaam” merupakan Puskesos “berkembang,” yang kinerjanya “cukup efektif” dalam mencapaian tujuannya. Saran: (1) Hendaknya jadi lembaga layanan terpadu satu pintu di tingkat desa; (2) Segera melakukan penjangkauan dan pendataan agar keluarga miskin terdaftar di DTKS, (3)  Tidak hanya mensosialisasikan program Kemensos, tetapi juga kementerian lain, dunia usaha, dan masyarakat; (4) Mampu memberi layanan langsung; (5) Program tidak hanya PSPK, tetapi juga rehabilitasi sosial dan pemberdayaan sosial; (7) Ada perwakilan SKPD di Puskesos; dan (7) Manajer sebaiknya pejabat tinggi pratama agar mampu mengkoordinasi kepala SKPD Kabupaten.
The technical features of designing multi­channel systems of the fifth generation
Authors:   State University of Telecommunications, Vlasov O. M. , Turovsʹkyy O. L.
Published: July 2021

At present, the standardization of mobile communication technologies to lay the foundations of wireless networks 5G, there is a general view of the need to replace the fundamental OFDM technology at the expense of more efficient, which can better operate in 5G conditions. For this purpose, a number of new forms of modulation have been introduced. It should be noted that at the same time, these methods have a basic principle of OFDM technology. The main idea of OFDM technology is to divide the frequency selective channel into a number of narrowband sub-channels. In these subchannels or subcarriers, orthogonal narrowband signals are transmitted in parallel. Since each of these signals undergoes shallow fading, then a fairly simple scalar correction of the channel. The main methods of promising technologies UF-OFDM, FBMC, and GFDM are described, which are logical continuation of OFDMmodulation development. In many ways, FBMC has much in common with CP-OFDM and OFDM, which use a cyclic prefix as a security signal. GFDM is a flexible multi-carrier transmission method, which is largely similar to OFDM. UF-OFDM uses filtering to provide its unique characteristics. An analysis of the prospects for the development of MIMO standards is presented. It is shown that the MU-MIMO specification is one of the most significant technological improvements to MIMO. The MU-MIMO specification is the evelopment of MIMO technology and an attempt to solve the problem of the growing amount of data transmitted over wireless networks. Thanks to it, the entire bandwidth of the network can be effectively used, and users will be able to exchange data at a speed of gigabytes per second. It has been established that the system of antenna chains from four to four and three users is the most productive and effective. The essence of the method of reducing the interval of monitoring the carrier frequency of the synchronization system of the domodulator, based on the use of sliding FFT, which can be proposed in the implementation of the above signal modulation technologies.
Information technology for developing a knowledge base for automated solution of problems in the process of planning and organization of an air strike on anyone’s objects
Authors:   Kharkiv National Air Force University, Samokish A. V. , Vorobyov Ye. S. ,   Kharkiv National Air Force University, Berdnik P. G. ,   V. N. Karazin Kharkiv National University
Published: July 2021

The article proposes an information technology for the development of a knowledge base for the automated solution of problems in the planning and organization of an air strike against enemy targets, using fuzzy sets and fuzzy logic. A formal presentation of information technology was performed using the IDEF0 functional modeling methodology. The use of a single hardware and software platform in the form of a set of standard platforms and unique architectural layers corresponding to the studied subject area will provide full control over the fuzzy neural network and achieve their benefits through the use of training and will increase the efficiency and validity of decision making. In the process of assessing the situation and making a decision, the commander seeks to present (predict) the dynamics of the future battle. This is necessary in order to develop an optimal plan of action, a reasonable allocation of forces and resources, as well as to determine measures for the rational implementation of the combat mission. The difficulties associated with planning the actions of aviation units for various tactical purposes are most evident in the operations of inflicting damage on enemy ground targets. The task of defeating which is one of the main for strike aircraft. The ground target is an extremely complex and multifunctional dynamic system that combines objects that solve various functional tasks. Planning of actions of aviation forces and means when striking ground targets requires the development of an optimal (in terms of the accepted criterion of optimality) scenario of their application, which provides for spatial and temporal coordination of aircraft from the aviation group. The most complete such coordination can be ensured through the use of a set of models that most adequately describe the space-time state of all aircraft, conditions and results of the use of aircraft.
Research of machine learning methods and their application for forecasting use outflow by telecommunications services
Authors:   State University of Telecommunications, Zhebka V. V.
Published: July 2021

The article examines the problem of outflow of customers of telecommunications companies: foreign and Ukrainian. It is determined that it is appropriate for companies to use information systems that will predict the behavior of users of services, and will warn the company in the presence of risks. It is established that foreign companies are more progressive in research and customer retention. In Ukrainian companies, unstructured data research tools are outdated. In order to expand the tools of Ukrainian companies, the achievements of foreign scientists have been studied. When processing a large amount of information in order to build short- and medium-term forecasts of consumer behavior, it is appropriate to build models of user behavior and use machine learning methods. It is established that scientists prefer the method of random forest. The methods of machine learning are analyzed in the work: their advantages and disadvantages are determined. The characteristics of the random forest method are investigated. It is established that further improvements in this area may be compositions of algorithms. The method of composition of algorithms — boosting is investigated. Its advantages and disadvantages are established, features of this method are defined. The stages of building a model for creating a forecast are defined. Based on the analyzed literature on the outflow of users, proposals have been identified that can reduce the reduction in their number. The priority directions of further researches concerning optimization problems of methods of machine learning, in particular in the conditions of uncertain factors are established.
Artificial neural network applications for data compression in video data transfer protocols
Authors:   State University of Telecommunications, Kis G. Ya. , Cherevyk V. M. ,   State University of Telecommunications
Published: July 2021

The article describes the current state of data transfer protocols and methods of image and video compression through the use of artificial neural networks, namely convolutional multilayer networks and deep structured learning. Based on recent publications, a comparative analysis of the performance of classical compression methods and methods based on neural networks was performed. The most effective are those compression methods which are based on decorrelation transforms, namely discrete cosine (JPEG standard) and wavelet (JPEG-2000 standard) transforms. The transform coefficients have a well-understood physical content of spatial frequencies and can be further quantized for a more optimal representation of components that are less important for human perception. The HEVC standard guarantees a more efficient image compression scheme that further takes advantage of the similarity of adjacent blocks and uses interpolation (intracoding). Based on the HEVC standard, the BPG (better portable graphics) format was developed to be used on the Internet as an alternative to JPEG, which is much more efficient than other standards. An overview of the current state of open standards, provided in the article, gives an explanation of what properties of neural networks can be applied to image compression. There are two approaches towards the compression using neural networks: in case of the first approach neural network is used as a part of an existing algorithm (hybrid coding), and in case of the second approach the neural network gives a concise representation of the data (compression network). The final conclusions were made as regards to the application of these algorithms in H.265 protocol (HEVC) and the possibility of creating a new protocol which is completely based on the neural network. Protocols using neural network show better results during image compression, but are currently hard to be subjected to standardization in order to obtain the expected result in case of different network architects. We may expect and predict an increase in the need for video transmission in the future, which will bump into the imitating nature of classical approaches. At the same time, the development of specialized processors for parallel data processing and implementation of neural networks is currently underway. These two factors indicate that neural networks must be embedded into the industrial data standards.
Analysis of methods for organizing user rights in GNU\Linux systems
Authors:   State University of Telecommunications, Storchak K. P. , Kravetsʹ D. V. , Tushych A. M. , Sorokin D. V.
Published: July 2021

This article is about user’s rights to files or directories. The GNU\Linux systems have many great security features, but one of the most important is the file permissions system. Methods for organizing user rights in GNU\Linux systems, such as granting rights to each user individually and grouping users with the same or similar rights into groups, are discussed. The concept of operating system user and superuser is formed. The benefits of grouping users by access level have been identified. The criteria for dividing users into groups are analyzed, depending on the format of computer use, the structure of the organization that owns a particular computer and the number and positions of people who will work with it. Also, the benefit of the mechanism of organizing users into groups to manage service users of services running in the system is considered. It is said that any file and directory in Linux has an owner user and an owner group. That is, any file and directory belongs to some system user and some group. In addition, any file and directory has three access rights groups: one for the owner user, one for members of the owner group, and one for all other users on the system. Each group consists of the rights to read, write and execute the file for execution. The format of saving rights to a file or directory and the mechanism of checking access to a file or directory are considered. An explanation is given of what the right to read, the right to modify and the right to execute means for the file and for the directory. It is with the help of these sets of permissions that the permissions of files in linux are established. Each user can only have full access to files that he owns or those that he is allowed to access. Only the Root user can work with all files, regardless of their set of permissions.
Integral indicator of adjustment parameters estimation of adaptive antenna arrays for telecommunication networks of information systems
Authors:   State University of Telecommunications, Plyushch O. G. , Vyshnivskyi V. V. ,   Taras Shevchenko National University of Kyiv, Tolyupa S. V. , Prokopov S. V. , Ishcheryakov S. M.
Published: July 2021

Adjustment speed is one of the main operation features of adaptive antenna arrays with the steepest descent gradient algorithm in telecommunication networks of information systems. Traditionally, estimation of the transient processes involves a computer simulation of the adaptive antenna array according to the selected noise environment. Substantial time required to create a respective model, big computational load that leads to quite a long period of time for performing required mathematical operations, as well as limited possibilities of simulation results interpretations are among the main drawbacks of the traditional approach. The paper proposes an integral indicator of adjustment parameters estimation of adaptive antenna arrays optimized according to the root-mean-square criterion and that does not require performing of the time consuming computer simulation of the transient processes. Integral indicator assumes values from 1, which corresponds to the quickest adaptation process, to 0, which indicates an absence of adaptation, and is built with account of the eigenvalues distribution of the array correlation matrix, squares of direction cosines of the optimal weight vector on the eigenvalues of the antenna array correlation matrix and the trace of this matrix. Computer simulation helped to establish that the designed indicator permits to correctly predict the speed of the transient processes in adaptive antenna arrays and perform their comparative analysis for different noise environments. Additionally, computation data, which are used for obtaining this indicator, allow us to clearly explain the character of the transient processes in the adaptive antenna arrays.
Method of developing machine learning architecture for IoT­devices based on serverless architecture
Authors:   State University of Telecommunications, Grynkevych G. O.
Published: July 2021

With the advent of IoT and microservice architectures, a multitude of intelligent distributed applications have emerged in which IoT devices collect, transform, and analyze data in large volumes and at high speed. A large number of these programs require robust, predictive analytics in real time, which require threading workflows closer to the data source, as well as dynamic resource management decisions. Moreover, predictive analytics requires the developer to create robust deep learning models, which, in turn, requires them to develop functions, find and configure parameters, and select machine learning models, which takes not only time, but also requires high experience level. The proliferation of machine learning libraries and frameworks, data ingestion tools, streaming and batch processing engines, rendering techniques, and the myriad of available hardware platforms further exacerbate these challenges. To overcome these complex challenges faced by developers of intelligent IoT applications, this article proposes a method for deploying machine learning architecture for IoT devices based on a serverless architecture called MLAbosa. The MLAbosa method can deploy, plan and dynamically manage data transfer tools, streaming software, batch analytics tools, and visualization tools across the cloud spectrum. This article describes the architecture of the MLAbosa method, highlighting the problems it solves.
Improving the efficiency of using cloud services by implementing IEEE 802.11ах
Authors:   State University of Telecommunications, Vyshnivskyi V. V. , Katkov Yu. I. , Kargapolov Yu. V. , Berezovska Yu. V. , Blagodyr S. O.
Published: July 2021

This article discusses one method for improving the efficiency of an information system that is capable of providing cloud services. The topic is relevant, because over time, more and more users are switching or planning to switch to cloud services. To consider methods for increasing the efficiency of an information system, an analysis is made of saving user funds and resources, ways of creating the possibility of remote access to services, methods of obtaining the possibility of using individual services at a certain level of abstraction in order to match these services to various user needs. The task is to study methods of increasing the efficiency of the use of cloud services by introducing IEEE 802.11ax technology and determining the directions and prospects of its use. To achieve the goal, empirical methods were used in the analysis of services, signs for their classification are determined, namely: a data storage or backup service; On-line office; On-line accounting; specialized Internet applications; closed private clouds for team management and customer relationship management; combinational services; applied cloud services. The advantages of cloud services are determined: scalability, flexibility, relevance, ease of access. Defines the cloud computing front-end and back-end architecture. This makes it possible to formulate the requirements for telecommunication access facilities to provide cloud services, as far as possible, namely: good quality of connection in places with a high density of users; creation of a Wi-Fi network with high bandwidth and low latency; support for previous versions of Wi-Fi devices; expansion of application in IoT networks; application of Wi-Fi infrastructure in target markets; creation of applications for IoT using technology and management of the parameter of the target wakeup time (Target-Wakeup Time); application for creating virtual reality (Virtual reality, VR); application to create augmented reality (AR); application for providing video content in Ultra HD mode; application in real-time applications, significant energy savings in the connected device. An analysis is performed of Wi-Fi technologies that are capable of meeting the specified requirements. It is concluded that this is possible when using the IEEE 802.11 standard.
Мethod of automated development of solutions for special cases in flight
Authors:   Flight Academy of the National Aviation University, Kolesnyk A. V. , Zakharchenko I. V. ,   Kharkiv National Air Force University, Tarasov R. V. ,   Kharkiv National Air Force University, Berdnik P. G. ,   V. N. Karazin Kharkiv National University
Published: July 2021

The article develops a method of automated decision making in the framework of the creation of DSS air traffic controller. The method of automated decision-making for special cases in flight is being developed as one of the stages of information technology for the creation of decision support system for air traffic controllers. This is necessary to help decide on the option of terminating the flight in the event of a special case in flight on the example of engine failure on the aircraft. The developed method involves the use of probabilistic programming technology. It includes: construction of a probabilistic hierarchical model of emergency based on the Bayesian network taking into account the factors influencing the decision-making process, creating a sample of examples for learning the model to improve future situations models on examples using the Bayesian learning paradigm, the choice of inference algorithm to obtain a probabilistic conclusion. The proposed method is implemented in the probabilistic programming system Figaro, which is free and available under an open source license. The program code is written in Scala. The set of training data was formed based on the results of the investigation of aviation accidents and catastrophes and contained fifty-two cases of forced landing at the aerodrome and on the site with different consequences. The learning process was learning the parameters of the model on the data and was performed on thirty- six examples. Other cases (sixteen) were used to test the prediction quality of the created model. The Bayesian learning paradigm is used to teach the model, which does not require a special learning algorithm and is performed using the inference algorithm. The Metropolis-Hastings approximation algorithm is used as the derivation algorithm. The developed method showed high accuracy of forecasting. The error between the actual result and the estimate obtained using the Bayesian network was 10%. Further research will be aimed at developing information technology for the creation of DSS air traffic controller for special cases in flight.
Artificial intelligence applications for project management
Authors:   State University of Telecommunications, Polonevych O. V. , Sribna I. M. , Mykolaychuk V. R. , Tkalenko O. M. , Shkapa V. V.
Published: July 2021

According to statistics, most projects (especially in the field of IT) are completed late, with budget overruns, or not completed at all. That is why new methods are being developed and the possibilities of applying new technologies for project management are being considered. The most promising in this regard is the use of artificial intelligence. The concepts and algorithms of artificial intelligence are widely discussed in terms of their potential for automation in business, industry and society. At first glance, project management seems less suitable for automation due to the inherent uniqueness of projects by definition. However, artificial intelligence is also opening up new possibilities for project management applications. This article will provide an overview and assessment of how artificial intelligence can be used in project management and how it can help project managers in their day to day work. A list of the main software products for project management, in which artificial intelligence technologies are integrated, with an indication of their functionality is given. It’s safe to say that with the advent of artificial intelligence, project managers will be able to optimize their efforts to accelerate the success of their product. At this point, the evolution of project management using artificial intelligence and bots is just beginning, but soon it will really change the way we manage projects. The analysis shows that the use of artificial intelligence technologies for project management will be especially effective in cases of complex projects that involve processing and analyzing large amounts of data for decision making. Obviously, using artificial intelligence will automate mundane, simple tasks like estimating an hour, scheduling a project, assigning the most effective team members, distributing risky information on a project, etc. But in terms of team management, conflict management, stakeholder management, artificial intelligence is not will replace the human qualities of the project manager.
Technologically neutral architecture as a component telecommunications operator management systems
Authors:   State University of Telecommunications, Berkman L. N. , Varfolomeieva O. G. , Salo A. Ya. , Strelnikov V. I. , Fokin V. I.
Published: July 2021

Information business and operations support systems nowadays are important and relevant topic in management of an operator activities and telecommunications provider. In the article we describe Basic requirements for system management activities of telecommunications operators defined. Particular properties of NGOSS architecture and its main components analyzed and formulated a common approach for the implementation of NGOSS methodology for management of telecommunications operator activities. The main components of the concept of NGOSS (New Generation Operations Systems and Software — a new generation of operating systems and software) are considered. TNA provides separation of external business process description from internal implementation. The necessity of introduction of technologically neutral architecture in the system of management of activity of the telecommunication operator for increase of labor productivity and decrease in operational expenses in telecommunication networks is substantiated. The application of the TNA architecture ensures that confidential information generated by or relating to the user is adequately protected against misuse or unauthorized misappropriation. TNA model (technologically neutral architecture) and SOA (service-oriented architecture) described as the mechanisms for interaction between business-processes and information data model. The main benefits of implementing technologically neutral architecture in the management system of telecommunications operator determined.ht up the issues related to the efficient management of the activities of the telecommunications operator. Interfaces do not depend on the hardware platform, operating system or programming language in which the service is implemented. This approach allows you to create services on different systems that interact with each other in a single standard way. The main perspectives of NGOSS (business, system, implementation; deployment), through which the life cycle of NGOSS is carried out, are considered. The expediency of implementing the NGOSS concept in the activity of a telecommunications operator is substantiated.
Оverview of the standard library for creating a GUI in Python
Authors:   State University of Telecommunications, Kravetsʹ D. V. , Tushych A. M. , Shkapa V. V. , Mykolaychuk V. R.
Published: July 2021

This article discusses the standard library for creating graphical user interfaces in Python. The relevance of graphical user interface creation tools, the value of the graphical user interface, the latest research and publications related to the tkinter library, the history of the library, the main widgets and geometry managers were analyzed. All the functions responsible for placing the elements of the graphical interface in the window are considered. There are three functions for placing widgets in the window — pack (), grid () and place (). Conclusions are drawn about the disadvantages and advantages of this library. The standard Python GUI library is closely related to the long-known and widely described Tk library, but the most relevant source of information will always be the library documentation on the Python programming language documentation site. The purpose of this article is to review the standard library for creating graphical interfaces in Python. Tkinter is a multi-platform graphical interface library based on Tk tools (widespread in the world of GNU/Linux and other UNIX-like systems, ported to Microsoft Windows, Apple Mac OS), distributed with open source, written by Wall Lumholt and Guido van Rossum. Included in the standard Python library. Tk has long been an integral part of Python. It provides a robust and platform-independent set of tools for windows that is available to Python programmers. However, in terms of usage, Tkinter is relatively easy compared to other libraries. This is a great choice for creating GUI applications in Python, especially if the modern look is not a priority for the program, and a big role is played by functionality and cross-platform speed.
Development and training of neural networks for character recognition
Authors:   State University of Telecommunications, Bukov R. D. , Shcherbyna I. S. , Nehodenko O. V. , Tykhonov Ye. S.
Published: July 2021

This article discusses the problem of the application of neural networks for character recognition, as well as the problem of developing methods and algorithms for the synthesis of neural networks. To solve the problems of optimizing the character recognition system, highly intelligent systems based on artificial neural networks are often used. However, artificial neural networks are not a tool for solving problems of any type. They are unsuitable for tasks such as payroll, but they have an advantage for character recognition tasks that conventional personal computers do poorly or not at all. It has been proven that artificial neural networks can be used for predictive modeling, adaptive control and applications where they can be trained using a dataset. Experiential self-learning can occur in networks that can draw inferences from a complex and seemingly unrelated set of information. The application of neural networks for solving practical problems in the field of character recognition and their classification is shown. It has been established that images can denote objects of different nature: text symbols, images, sound samples. When training the network, various sample images are offered with an indication of which class they belong to. At the end of training the network, you can present previously unknown images and receive an answer from it about belonging to a certain class. The topology of such a network is characterized by the fact that the number of neurons in the output layer, as a rule, is equal to the number of conditioned classes. This establishes a correspondence between the output of the neural network and the class it represents. A method for training a neural network is proposed, according to which the person managing the network takes a direct part in training the network, it itself sets the reference images of all symbols, as well as distorted images of the standards (plagued copies).
Development of machine learning algorithms for a recommendation system for selecting musical compositions
Authors:   State University of Telecommunications, Demydov D. D. , Shcherbyna I. S. , Trintina N. A. , Shtimmerman A. M. , Ishcheryakov S. M.
Published: July 2021

The article analyzes the method of singular value decomposition (SVD) as an effective way to build a recommender system. With the development of information technologies and their introduction into public life, there is a need to search for accentuated information in conditions of uncertainty. To solve such problems, recently created intelligent recommendation systems [1]. The popularity of recommendation systems is growing in every segment of goods and services, in particular music. From a socio-economic point of view, such systems are the main tool for the dissemination of new compositions in the field of music promotes the promotion of these compositions in accordance with the preferences of the target audience and encourages users to purchase new music tracks. In addition, such systems significantly reduce the time and facilitate the search for appropriate musical compositions under conditions of uncertainty. The main problem in developing machine learning algorithms is the lack of an individual approach to each user. All recommendations are based on the statistical behavior of the majority, resulting in a percentage of people who do not receive recommendations that match their personal preferences. In the case of a separate analysis of each of the users and the implementation of recommendations in accordance with their personal use of Internet resources, the number of quality and more accurate proposals in the list of recommendations would increase significantly. Machine learning methods are effectively used to build recommendation systems, namely: the k-nearest neighbors method, the Bayesian algorithm and the singular matrix decomposition method. Among these methods, the SVD method is the most widely used in practice. This method is used to reduce the number of non-significant data set factors. Factors in recommendation systems are properties that describe the user or subject. In music recommendation systems, this can be a genre. SVD reduces the dimension of the matrix by removing its hidden factors.
Transdisciplinary consolidation of information invironments
Authors:   National Center ", Honchar А. V. ,   Junior Academy of Sciences of Ukraine", Stryzhak O. Ye. ,   National Center "Junior Academy of Sciences of Ukraine", Berkman L. N. ,   State University of Telecommunications
Published: July 2021

The paper discusses an ontological approach to solving the problem of integrated use of Big Data through transdisciplinary semantic consolidation of information resources. The category of taxonomy is considered as a constructive for the formation of consolidated information, taking into account its semantics. The formation of a hyperset of taxonomies — taxonomic diversity — implements the consolidation of information resources, defined as a verbal-active function of interpreting a set of binary relations between all contexts reflecting the meanings of concepts that form the content of subject areas, whose information resources are involved in network interaction. The category of information consolidation, as a taxonomic diversity of information resources, is characterized by the existence of verbally active reflection and recursion. The concept of discourse is defined as the inter-contextual connectivity of network information resources, which is represented by verbal-active reflection, on the basis of which taxonomic diversity is realized. For consolidated network information, the format of narrative discourse is determined. The concept of an arbitrary taxonomy is defined as a term, which makes it possible to implement the process of forming taxonomies based on the use of sets of λ-terms. The topology of interaction of taxonomy concepts sets is represented as a set of marked Böhm trees. An example of the formation of the information resources consolidation in the study of historical and cultural heritage with the display of museum expositions in the format of 3D panoramas is given. An algorithm for the consolidation of 3D models of heritage conservation objects with network GIS services and network information resources is given.
Statistical models of network traffic
Authors:   Lutsk National Technical University, Yakymchuk N. M.
Published: July 2021

The article considers the issues of statistical modeling of traffic in telecommunication networks with packet switching. The simulation results are used in the development of network technical condition management systems, in particular, diagnostics, troubleshooting and network configuration management. The peculiarities of congestion control of separate network segments are emphasized. With improper analysis the overload condition can be mistaken for equipment failure. Therefore, control and elimination of congestion is a statistical task. The concept of end-to-end network diagnostics is considered. This concept provides for effective assessment of the quality of functioning of all network components taking into account their interrelationships. The main issues are the interaction of equipment, inefficient configuration, improper network organization and user operation. Methods of traffic statistical control characteristics based on perforated and marker bucket algorithms are analyzed. A feature of these algorithms is the formation of a strict output stream at a rate that does not depend on the non-uniformity of the input stream. The possibility of improving the token bucket algorithm by adapting to changes in the statistical characteristics of traffic is shown. To solve this problem, statistical mathematical models of network traffic are built. Data traffic circulating in telecommunication networks by packet switching has self-similar (fractal) properties. The self-similar process retains its properties when considered at different time scales (invariance to scale changes). The degree of statistical stability of the process with multiple scaling is determined by the Hirst parameter (the self-similarity parameter). Graphs of statistical characteristics of low-speed and high-speed data traffic are obtained. Their comparative analysis is carried out.
Improve continuous integration and delivery methods by implementing a load testing stage
Authors:   State University of Telecommunications, Bereznyuk A. V. , Makarenko А. О. , Grynkevych G. O. , Lazebnyy S. G.
Published: July 2021

The contradiction between system stability and development speed development introduces new challenges to processes automatization. Significant increase of quality and speed of software development was reached due to agile method and continuous integration and continuous delivery (CICD) approach, which enabled rapid software changes by breaking development process into small iterative stages. New product version with new features incorporated is the result of each iteration. Then, there are automation tools typically used for testing and building. However, there is space for performance issues and delivery failures in this scheme. System scaling is generic approach for resolving performance problems, but the question how much the system should be scaled remains unanswered. Load testing procedure is commonly used but it is still not perfect, as testing environment is very different from production environment. Therefore, current paper is aimed at overcoming described difficulties by extending CICD approach with load testing automatization, system benchmarking, which allows system interruption minimization, and system scaling evaluation by scale factors calculation. Using these enrichments more precise testing result will be provided. We also suggest using such tools as Go-replay for traffic mirroring and Nagios for monitoring. Hence, this paper suggests enriching and increasing the efficiency of CICD approach. In addition, paper addresses methods of monitoring metrics collecting in centralized system. They will be used in further analysis and decision-making process regarding new product version in the automated mode.
Development of a system for the security assessment for smart homes based on the IoT
Authors:   State University of Telecommunications, Halay Ya. O. , Bondarchuk A. P. , Tkalenko O. M. , Polonevych O. V. , Zinchenko O. V.
Published: July 2021

This article is about developing a security assessment system for smart homes that use Internet of Things technology. The Internet of Things (IoT) is a nascent paradigm focused on the relationship of things or devices to each other and users. Over time, most connections on the Internet of Things go from «people interact with things» to «things interact with things». This technology is expected to be an important milestone in the development of smart homes to bring convenience and efficiency to our lives and our homes. But the introduction of this IoT technology in our homes will be important for the safety of these technologies. Connecting all smart objects inside the house to the Internet and to each other leads to new security and privacy issues, such as the confidentiality, authenticity, and integrity of the data that is perceived and exchanged. These technologies are very vulnerable to various security attacks that make a smart home based on IoT unsafe to live in, so security risks need to be assessed to assess the situation of smart homes. For any technology to be successful and widely used, it must gain the trust of users, ensuring sufficient security and confidentiality. As in all sectors, maintaining security will be the most important challenge to overcome. As homes become more computerized and filled with devices, potential computer security attacks and their impact on residents need to be investigated. This paper uses a methodology that focuses mainly on information assets and examines containers (technical, physical and human) and conducts security risk assessments to highlight various security vulnerabilities in the smart home based on the Internet of Things, the consequences and proposing measures against identified problems. that meet most safety requirements. Finally, it offers recommendations for users.