Journal articles on the topic 'Технологія Data Mining'
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Chagovets, L. O., V. V. Chahovets, and A. S. Didenko. "The Data Mining Technology Applications for Modeling the Unevenness of Socio-Economic Development of Regions." Business Inform 3, no. 506 (2020): 82–91. http://dx.doi.org/10.32983/2222-4459-2020-3-82-91.
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Твердохліб, Іван Петрович. "Технологія "data mining" як інструментальний засіб удосконалення методології прогнозування соціально-економічних процесів." Актуальні проблеми економіки, no. 12 (2008): 247–58.
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Клочко, Оксана, and Олександр Михайлюк. "SMART-ТЕХНОЛОГІЯ В МОДЕЛЮВАННІ МІЖПРЕДМЕТНИХ ЗВ’ЯЗКІВ МАТЕМАТИКИ ТА ІНФОРМАТИКИ." Науковий вісник Інституту професійно-технічної освіти НАПН України. Професійна педагогіка, no. 17 (December 27, 2018): 34–42. http://dx.doi.org/10.32835/2223-5752.2018.17.34-42.
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Пріоритетним напрямом розбудови системи освіти нового покоління є впровадження принципів відкритої освіти шляхом розробки електронних освітніх ресурсів із використанням SMART- технологій. У статті розкрито цілі, зміст і шляхи розв’язування проблеми моделювання процесу забезпечення міжпредметних зв’язків математики та інформатики із використанням комп’ютерно орієнтованих систем; побудовано функціональну схему макроблоку розроблення електронного навчально-методичного комплексу навчальної дисципліни.
Процес розроблення електронного навчально-методичного комплексу пропоновано здійснювати шляхом використання користувачем (викладачем) можливостей блоку формування та розбудови контенту навчальної дисципліни на основі інтелектуальних алгоритмів Data Mining, макроблоку моделювання процесу навчання, електронних ресурсів метадисципліни, макроблоку пошуку, макроблоку онлайн-консультування. Реалізація метадисциплінарного підходу дасть змогу застосовувати механізми інтеграції (поєднання, взаємопроникнення, взаємозближення, утворення взаємозв’язків) та систематизації даних різних навчальних дисциплін. Планування міжпредметних зв’язків здійснюється за допомогою побудови мережевого графіка, що є формою представлення моделі навчального процесу. З метою побудови календарного графіка забезпечення міжпредметних зв’язків пропонуємо використовувати комп’ютерно орієнтовані системи інформаційно-динамічного моделювання, що дасть змогу забезпечити автоматизацію багатьох функцій управління навчальним процесом. У дослідженні за основу було взято продукт Microsoft Corporation – Microsoft Project 2016. Такі напрями реалізації SMART-технологій у моделюванні процесу навчання дадуть викладачеві можливість: визначити найбільш ефективні підходи до вирішення завдань забезпечення міжпредметних зв’язків математики та інформатики; на основі створених мережевих (календарних) графіків розробити моделі процесу забезпечення міжпредметних зв’язків; здійснювати управління процесом навчання на основі створених мережевих моделей та відслідковувати міжпредметні зв’язки, необхідні для оптимізації планування навчального процесу.
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Sugoniak, Inna I. "OLAP-ТЕХНОЛОГІЇ ДЛЯ МОНІТОРИНГУ УСПІШНОСТІ СТУДЕНТІВ ЗА УМОВ РЕЙТИНГОВОЇ СИСТЕМИ ОЦІНЮВАННЯ ЗНАНЬ." Information Technologies and Learning Tools 38, no. 6 (December 12, 2013): 245–56. http://dx.doi.org/10.33407/itlt.v38i6.924.
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У статті висвітлені проблемні аспекти впровадження інформаційних технологій у освітню діяльність вищих навчальних закладів, визначені завдання комплексного моніторингу успішності студентів, проаналізовано сучасні технології багатовимірного аналізу даних зокрема, концепція Data Mining і OLAP-технології, визначені можливості й напрямки використання засобів багатовимірного аналізу даних у системах моніторингу успішності студентів, виконано об'єктно-орієнтоване проектування програмного комплексу системи з використанням мови UML, обґрунтований вибір платформи реалізації й наведено опис прототипу системи.
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Loginova, Lyudmila N., and Alexander M. Shash. "Data Mining technologies in managing the assortment of trading companies." Journal of Applied Informatics 16, no. 91 (February 26, 2021): 99–109. http://dx.doi.org/10.37791/2687-0649-2021-16-1-99-109.
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In the conditions of fierce competition, satisfaction of all customer needs provides a trading enterprise with a sustainable competitive advantage. With the traditional structure of the assortment, there is a decrease in both the potential and real level of profit, the loss of competitive positions in promising markets, and, therefore, there is a decrease in the stability of the enterprise. The development of an analysis system to determine the specifics of the product range, optimize the range, and adapt it to the conditions of the Russian market is undoubtedly an urgent task. This article provides an overview of trade and IT companies that use data mining technologies. The survey showed that many companies are using data mining technology to improve customer service, turnover and sales in stores. In this regard, the management of Familia decided to develop its own software that will combine the analysis of turnover and sales in the company's stores in order to increase sales and improve the placement of goods in stores so that the client buys the necessary things, increasing the company's profit. The paper shows the possibility of combining several data mining methods in one system; shows the results of the analysis system and shows the effectiveness of the developed analysis system at Familia. The uniqueness of the developed software is the combination of data mining algorithms into one software product. The developed analysis system, based on the joint work of two data mining algorithms K-means and Apriori, allows you to manage the range of trade enterprises, reducing company losses.
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Мороз, Б., Л. Кабак, A. Ширін, and С. Овчаренко. "Використання Data Mining в інформаційних бібліотечних системах." COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, no. 42 (March 31, 2021): 177–84. http://dx.doi.org/10.36910/6775-2524-0560-2021-42-26.
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В даний час для аналізу даних використовуються алгоритми та інструменти для аналізу даних, які називаються Data Mining. Data Mining успішно використовується в різних галузях промисловості. У статті розглядається можливість впровадження цієї технології в бібліотечні системи, оскільки аналіз даних можна використовувати для отримання різних прогнозів. Сучасні технології надходять і до бібліотек. Для запобігання дефіциту книг, та запобігання переповнення бібліотеки застарілими книгами ми можемо використовувати інформаційну систему з функціями аналізу даних з інтеграцією інструментів аналізу даних у системи управління ризиками, які можуть допомогти отримати корисну інформацію з бази даних з метою прийняття рішення про списання книг або переміщення в сховище.
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Samarkin, M. E., and V. N. Tarasov. "Telecommunication company big data classification by data mining technique." Infokommunikacionnye tehnologii 14, no. 3 (September 2016): 258–63. http://dx.doi.org/10.18469/ikt.2016.14.3.05.
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Расулев, Абдулазиз, and Баходир Исмоилов. "Организационно-правовые аспекты применения цифровых технологий в противодействии коррупции: зарубежный опыт правоприменительной практики." Общество и инновации 1, no. 2 (November 18, 2020): 300–320. http://dx.doi.org/10.47689/2181-1415-vol1-iss2-pp300-320.
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В статье рассматриваются опыт зарубежных стран в сфере применения цифровых технологий в противодействии коррупции. Определено, что в ряде иностранных государств наряду с уже апробированными технологиями (электронное правительство, информационные и краудсорсинговые платформы) активно внедряются современные информационные технологии такие как: технологии обработки больших объемов данных (Big Data), распределенной книги (DLT), блокчейн, интеллектуального анализа данных (Data Mining), интеллектуального анализа в сфере противодействия коррупции при проведении государственных закупок, аналитические инструменты для аудиторов (Forensic Tools), электронные системы верификации деклараций о доходах, расходах, активах и интересах государственных служащих, электронные технологии противодействия коррупции при осуществлении электорального процесса и др.
Определено, что преимущества цифровизации могут осуществляться только при наличии соответствующих инфраструктур, положений, финансовых ресурсов и персонала, подготовленного по вопросам ИКТ.
Обосновано, что процессы цифровизации правоохранительной деятельности способствуют повышению эффективности проводимой антикоррупционной политики, обеспечивают ее эффективность, объективность, позволяют снижению расходов на поддержание правопорядка, минимизируют влияние человеческого фактора в указанной сфере.
Отмечено, что технологии, основанные на нейронных сетях и децентрализованных, синхронизированных базах данных фундаментально изменят характер государственного управления и способны значительно снизить риски коррупционных правонарушений в будущем
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Okunev, Boris V., and Alexander S. Shurykin. "Solving the problem of calendar data preprocessing during the implementation of Data Mining technology." Journal Of Applied Informatics 15, no. 90 (December 28, 2020): 27–41. http://dx.doi.org/10.37791/2687-0649-2020-15-6-27-41.
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At the moment, dirty data, that is, low-quality data, is becoming one of the main problems of effectively solving Data Mining tasks. Since the source data is accumulated from a variety of sources, the probability of getting dirty data is very high. In this regard, one of the most important tasks that have to be solved during the implementation of the Data Mining process is the initial processing (clearing) of data, i.e. preprocessing. It should be noted that preprocessing calendar data is a rather time-consuming procedure that can take up to half of the entire time of implementing the Data Mining technology. Reducing the time spent on the data cleaning procedure can be achieved by automating this process using specially designed tools (algorithms and programs). At the same time, of course, it should be remembered that the use of the above elements does not guarantee one hundred percent cleaning of "dirty" data, and in some cases may even lead to additional errors in the source data. The authors developed a model for automated preprocessing of calendar data based on parsing and regular expressions. The proposed algorithm is characterized by flexible configuration of preprocessing parameters, fairly simple implementability and high interpretability of results, which in turn provides additional opportunities for analyzing unsuccessful results of Data Mining technology application. Despite the fact that the proposed algorithm is not a tool for cleaning absolutely all types of dirty calendar data, nevertheless, it successfully functions in a significant part of real practical situations.
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Burlakov, Alexandr, and Irina Mushenyk. "Theoretical Principles of Implementation and Use of Modern Technologies of Intellectual Data Analysis in Economy." Modern Economics 25, no. 1 (February 23, 2020): 27–32. http://dx.doi.org/10.31521/modecon.v25(2021)-04.
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Abstract. The aim of the article is to study the theoretical foundations of the introduction and use of modern technologies of data mining in the economy of Ukraine. Research methodology. The theoretical and methodological basis of the article were the works of leading foreign and domestic scientists on the evaluation of the effectiveness of the implementation and use of data mining technologies. Achieving this goal was carried out using the following scientific techniques and research methods: monographic (in reviewing and studying the literature on evaluating the effectiveness of data mining technologies), analysis and synthesis (for research and generalization of research results); logical-theoretical and dialectical (to form the conclusions of the study). In the process of research, the substantiation of theoretical calculations and conclusions was carried out on the basis of system-functional and structural approaches to the analysis of information flows and control systems of data mining technologies. The information base of the study is articles and monographs, including those posted on web pages. Results of the research. The theoretical bases of functioning of modern technologies of data mining in the information economy are systematized, and also questions of the basic directions of application of the Data Mining system are analyzed, namely as a mass product for business applications and as a tool for unique researches. Scientific novelty of research results. It consists in the theoretical substantiation of possibilities of introduction and application of modern technologies of intellectual analysis, in various branches of economy, as effective tools of providing the timely information for the management of business entities on the basis of which it is possible to make qualitative administrative decisions. The practical significance of the research results. The obtained results can be used for further prospective research of information systems of economic entities, which are created on the basis of modern data mining systems, as well as in the implementation of computerization tools for analytical and synthetic data processing of information systems in the enterprise. Keywords: information system; data mining; information technology; data mining.
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KRAVTSOV, Alexey, Vasily ANISCHENKO, Victor ATRUSHKEVICH, and Ivan PYTALEV. "PERSPECTIVES OF APPLYING WEBRTC FOR REMOTE-CONTROLLED MINING EQUIPMENT." Sustainable Development of Mountain Territories 12, no. 4 (December 30, 2020): 592–99. http://dx.doi.org/10.21177/1998-4502-2020-12-4-592-599.
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Currently a lot of mining companies, such as Caterpillar, Sandvik, Atlas Copco and Komatsu are developing solutions for machines remote control and mining process automation. The purpose of these technologies is to increase labor efficiency and safety. Solutions for remote control should establish secure connection and transfer data with low latency – this could be implemented with WebRTC technology. Several problems were revealed during open data analysis of Cisco, Sandvik, Moxa and Acksys remote control solutions – using of expensive IP-cameras, sophisticated network and security design. WebRTC could solve these and several other problems. WebRTC operation principles reviewed further: initial information exchange via signaling server, use of ICE for discovering shortest path between peers and establishing peer-topeer connection. This could simplify network design and allow to use more cheap USB cameras instead of IP-cameras. For security reasons WebRTC encrypts transmitted data with DTLS and SRTP algorithms. Encryption key fingerprints are exchanged over signaling server; after connection establishment, peers are exchanging keys itself over discovered route. But WebRTC specification does not define peer to signaling server communication, which may lead to breach in unsecure data channel, especially man-in-the-middle attack. To prevent this, software engineer should ensure that connection with signaling server is secure. Mining machine model was developed to test data transmission latency. In this model, Raspberry Pi single-board computer is responsible for wireless connection, video encoding and commands processing. Received commands are passed to Arduino controller, which operates electric engines controller. Three remote control scenarios were tested – model is near the operator and in direct line of sight; model is near operator, but not in direct line of sight; model and operator are far away from each other (over 1600 km), model controlled over Internet. Test results shows that transmission latency does not exceed 300 ms, which is suitable for real-time remote driving.
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Chereshnia, Olga. "Environmental load from use of blockchain technology and cryptocurrency mining in Russia." InterCarto. InterGIS 27, no. 1 (2021): 238–48. http://dx.doi.org/10.35595/2414-9179-2021-1-27-238-248.
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With the increasing use of information technologies (IT) their opportunities to ensure environmental sustainability and the risks of their widespread adoption are growing. And if the possibilities have been studied well enough, then the risks have been paid attention to relatively recently. However, awareness of these risks is becoming increasingly important with the spread of technologies. Currently, there are already hundreds of cryptocurrencies, and the technological basis for many of these currencies is the blockchain—a digital ledger of transactions. This article has assessed the environmental burden of mining and supporting transactions in the cryptocurrency market in Russia using CO2-equivalent. For this, for the first time, the amount of electricity consumed to support cryptocurrency transactions in Russia was calculated, data on the largest cryptocurrency mining centres were collected and systematized, and the main factors for the placement of both large and small private farms were determined. Based on the collected data a map of the spread of mining centres in Russia was created. Our analysis showed that on average, 2.977 million tons of CO2 equivalent are emitted in Bitcoin production in Russia, and the total emissions from cryptocurrency mining in Russia are 4.466 million tons of CO2 equivalent. Based on our data on environmental damage, we believe that when deciding on the use of blockchain technology, not only its capabilities should be taken into account, but also an assessment of the ratio of potential benefits and impact on the environment. A systematic understanding of interrelated direct and indirect impacts is needed to make decisions on the use of blockchain, since the technology shows itself as potentially one of the most energy and resource intensive.
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RYBAK, Jaroslaw, Marat KHAIRUTDINOV, Yulia TYULYAEVA, and Cheynesh KONGAR-SYURYUN. "RESOURCE-SAVING TECHNOLOGIES FOR DEVELOPMENT OF MINERAL DEPOSITS." Sustainable Development of Mountain Territories 13, no. 3 (September 30, 2021): 406–15. http://dx.doi.org/10.21177/1998-4502-2021-13-3-406-415.
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The relevance of the work is caused by the need to survive the mining industry during the protracted post-reform crisis and to minimize its negative impact on the ecology of the region through the development of technogenic mineral resources. Purpose of work. Substantiation of the possibility of replacing the traditional components of the filling composite with own or attracted man-made wastes after their processing to a level that meets the conditions of environmental safety and economic feasibility. Research methods: systematization, analysis and generalization of theoretical and experimental research in this area, as well as patent data. Results. A generalization is made, the result of an analysis of the mechanism and rates of accumulation of waste from mining and processing of mineral raw materials is given, and a multifactorial mathematical model of degradation of environmental ecosystems as a result of the impact of waste is formulated. A historical background is given and an assessment of the development of mineral deposits with backfilling with hardening mixtures based on utilized man-made waste in a closed cycle is given. A promising method of activating the binding components of the hardening mixture is recommended, treatment in a high-speed mill - disintegrator. The results of experimental studies of the possibility of using metallurgical slags of the Chusovoy metallurgical plant as a binder and as an inert filler of ore dressing wastes of PJSC Uralkali are given. It is shown that if the content of unrecovered metals in industrial waste is more than the background level, they can be disposed of after the extraction of metals within the framework of a single technological cycle of waste-free production. It is concluded that when preparing a filling composite, it is possible to replace traditional commercial components with man-made waste from mining and processing and metallurgical industries after extracting useful components from them and neutralizing hazardous impurities. The prospect of the transition of mining production to an innovative principle of organization, which excludes the storage of waste, is noted, for which it is advisable to combine physical-technical and physical-chemical technologies at the design stage in the technological process of resource development. Conclusions. The involvement of man-made waste in a closed production cycle increases the environmental and economic efficiency of enterprises. Conversion of production to minimize waste volumes and their use in their own or in related production is an effective step towards sustainable development of the mining region.
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RAPAKOV, GEORGIY G., VYACHESLAV A. GORBUNOV, VIKTOR B. ANKUDINOV, and ALEKSEY V. UDARATIN. "INTELLECTUAL TECHNOLOGY IN THE ASSESSMENT OF PSYCHOSOCIAL FACTORS OF POPULATION MEDICAL ACTIVITIES." Cherepovets State University Bulletin 5, no. 104 (2021): 35–45. http://dx.doi.org/10.23859/1994-0637-2021-5-104-3.
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The paper focuses on the study of methods to develop an associative model when performing data mining in the task of evaluating psychosocial factors of the population medical activity. A monitoring medical and sociological study was carried out, the object of which was the organization system of medical prevention at the territorial level. Related events were detected as a result of applying mining algorithms and methods. While assessing the psychosocial portrait of the students' parents, 25 association rules were identified with support from 80 % to 90 % and reliability above 97 %. It has been found that the vast majority of respondents ignore health-positive information materials and impacts by not being able to independently propose measures that correct traditional risk factors (RF). The results of the analysis were used to support management decisions in the regional medical prevention system.
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Khalimova, Sophia, and Anastasiya Ivanova. "Labor Productivity of Economic Sectors in the Regions: The Role of Information and Communication Technologies." Spatial Economics 17, no. 4 (2021): 69–96. http://dx.doi.org/10.14530/se.2021.4.069-096.
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The attention of this article is focused on the impact that expanding of the usage of information and communication technologies (ICT) has on the economic development of Russian regions. As shown by various authors, the use of ICT ultimately leads to an increase in the factor productivity. Here, we assess to what extent the use of ICT contributes to the growth of economic development efficiency at the regional level, which is interpreted here as labor productivity in certain economic sectors, and measured as output per worker. Panel data analysis for Russian regions covers 2015–2018. The analysis shows that the spread of ICT has a positive effect on labor productivity in both mining and manufacturing, with dividing regions into two groups – ‘resource’ and ‘non-resource’ depending on role of the extractive industry in regional economy – when considering labor productivity in mining. It was found that there is a relationship between ICT development indicators and labor productivity, with significant factors being industry and regionally specific. The widespread adoption of ICT has a positive effect on the economic development effectiveness, with a stronger link in the manufacturing, while for the mining the discovered relation was not so clear. Among the factors affecting labor productivity in the mining in ‘resource’ regions are access to the Internet, the use of ‘cloud’ services, as well as involvement in research and development; for ‘non-resource’ regions significant factors are the use of local computer networks, regional ICT subsidies, and the purchase of computing equipment. For the manufacturing, the key factors are access to the Internet, the share of high-tech businesses in the regional economy, the purchase of computing equipment, and the use of the services of third-party organizations and ICT specialists
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Popov, Anatoly, Michael Dorrer, Alexandra Dorrer, Elizaveta Trishkina, and Nikita Romanov. "An approach to building a predictive model of the life cycle of information resources based on stochastic gert-networks and process mining technology." Informatization and communication 4 (November 2020): 107–12. http://dx.doi.org/10.34219/2078-8320-2020-11-4-107-112.
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The article proposes an approach to predicting the numerical parameters of the life cycle of information resources. The main task of this work is to develop a tool for numerical forecasting of the life cycle of information resources based on actual life cycle data in the form of resource history event logs. The forecast is carried out using the apparatus of stochastic GERT networks. The construction of the GERT model is performed using the Process Mining algorithmic apparatus and the ProM software framework. The object of the analysis was the data of the Scientific Electronic Library Online. The data is publicly available on the Kaggle.com website. To build a GERT network describing the life cycle model of an information resource, we used the methods of intellectual analysis of Process Mining processes implemented using the ProM Framework. In the course of the work, an analysis of the life cycle of information resources of the Scientific Electronic Online Library was carried out. The paper presents the process of extracting data used to model a GERT network using the ProM framework. The data obtained made it possible to restore the topology of the stochastic network and identify the laws of probability density distribution of the duration of the life cycle stages. On the basis of the constructed GERT-network, the law of distribution of the probability density of the duration of the life cycle of an information resource was described. The obtained result confirms the applicability of Process Mining technology to probabilistic analysis and forecasting of the life cycle of information resources.
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Esmagambetov, T. U., M. I. Shikulskaya, and O. M. Shikulskaya. "СИСТЕМА ИНФОРМАЦИОННО-АНАЛИТИЧЕСКОЙ ПОДДЕРЖКИ УПРАВЛЕНИЯ ПРОЦЕССАМИ ЭКСТРЕННОГО РЕАГИРОВАНИЯ НА ЧС И ПОЖАРЫ." Engineering and Construction Bulletin of the Caspian Region, no. 4 (38) (December 30, 2021): 73–79. http://dx.doi.org/10.52684/2312-3702-2021-38-4-73-79.
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Авторами обоснована актуальность создания системы информационно-аналитической поддержки управления процессами экстренного реагирования на ЧС и пожары. Обоснован выбор аналитической платформы Deductor в качестве инструментария для создания системы. В результате исследования разработана Система информационно-аналитической поддержки управления процессами экстренного реагирования на ЧС и пожары на аналитической платформе Deductor. Система позволяет осуществлять многомерный анализ имеющихся оперативных данных. Для эффективного и наглядного представления и оперативного или углубленного анализа данных с использованием технологий OLAP и Data mining на платформе Deductror был разработан OLAP-куб, содержащий 15 измерений, 1 основной процесс и 7 фактов. Описание основных алгоритмов системы представлено на диаграммах, что обеспечивает более наглядное восприятие функционала системы, упрощает ее сопровождение и исключает неоднозначность интерпретации представленных на диаграммах материалов. Система анализа данных обладает широкими визуальными средствами. Выходные данные системы отображаются в форме графиков, в табличном виде и в виде OLAP-отчетов. Тестирование системы показало наличие значительного эффекта от ее использования.
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Stupnik, M. I., V. V. Peregudov, V. S. Morkun, T. A. Oliinyk, and M. K. Korolenko. "Development of Concentration Technology for Medium-Impregnated Hematite Quartzite of Kryvyirih Iron Ore Basin." Nauka ta innovacii 16, no. 6 (June 12, 2020): 56–72. http://dx.doi.org/10.15407/scin16.06.056.
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Introduction. Trends in developing Ukraine’s metallurgy in the context of using its mineral raw base indicate prospects for mining hematite quartzite deposits. Problem Statement. The problem of producing high-quality hematite ore concentrates is associated with the fact that aggregates of martite, goethite, marshallit quartz, and other low hard minerals can be easily reground while crushing and grinding. This results in increased content of fine particles (slimes), which decreases selectivity of separating ore and non-metallic minerals. One of the ways to solve this problem is gentle ore grinding Purpose. Developing a technology of dry and wet concentration for hematite quartzite from Kryvyi Rih Iron Ore Basin. Materials and Methods. While conducting the research, a set of methods are used including generalization of research data; chemical and mineral analysis of ore and concentration products prior to and after concentrating by magnetite and gravitation methods; mathematical modeling of processes; technological testing in laboratory and industrial conditions. Results. Magnetic and gravitation separation is used for hematite ore concentration. Sintering ore with Fe content of 55.1% and concentrates of 62.32-64.69% Fe have been produced from hematite ore. Iron extraction in marketable products makes up 73.6-80.49%. Conclusions. There have been developed technologies for dry and wet concentration for hematite quartzites of Kryvyi Rih Iron Ore Basin. For the first time, magnetic separation has been suggested to be used for hematite ore concentration. This has enabled producing concentrates with an iron content over 64.0%, decreasing ore grinding front by at least 40% as compared with the initial one, and reducing operation and capital expenses by over 30%.
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Prokopchina, Svetlana V. "APPLICATION OF BAYESIAN INTELLIGENT TECHNOLOGIES AND INTELLIGENT IIoT (IIIoT) IN THE MANAGEMENT OF CYBERPHYSICAL SYSTEMS UNDER CONDITIONS OF UNCERTAINTY." SOFT MEASUREMENTS AND COMPUTING 1, no. 5 (2021): 38–54. http://dx.doi.org/10.36871/2618-9976.2021.05.004.
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The effectiveness of the functioning of cyberphysical systems is based primarily on the use of powerful methods of obtaining and processing information. The complexity of the structures and properties of cybernetic systems, as well as the conditions of their functioning, determine special requirements for measurement methods and computing, performed in such systems. As a rule, the uncertainty of CPS models, as well as the uncertainty of the influence of environmental factors and their interrelations with the properties of systems, primarily define the requirements for the intellectualization of measurements and computational processing of information. In this article, methods and tools of Bayesian intelligent measurements (BII) are proposed to ensure the effectiveness of management of cyberphysical systems under conditions of uncertainty. The concept and methodology of creating an intelligent industrial Internet of Things (IIoT) is proposed, the distinctive feature of which is the intellectualization of measurement methods and data preprocessing. For this purpose, IIoT includes an intelligent DATALAKE, which is built on the basis of a Bayesian intelligent measurement systems that implements not only measurement and data integration functions, but also management decision support. Examples of real cyberphysical systems with control based on Bayesian intelligent measuring instruments are given. The prospects of using the proposed solutions based on BII in various modern technologies based on the principles of BIG DATA, DATA SCIENCE, neural networks, IIoT, DATA MINING and others are considered.
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Зеленчук, Н. А., and О. К. Альсова. "DESIGN AND IMPLEMENTATION OF AGRICULTURAL CLASSIFICATION SOFTWARE." Южно-Сибирский научный вестник, no. 1(41) (February 28, 2022): 51–59. http://dx.doi.org/10.25699/sssb.2022.41.1.008.
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В настоящее время в сельскохозяйственной отрасли наблюдается постоянное увеличение объемов получаемых данных, возрастает потребность в их качественной обработке и точных расчетах для принятия обоснованных решений. Поэтому особую актуальность приобретают задачи, связанные с разработкой алгоритмов, методов и программного обеспечения для решения задач анализа и обработки данных в области сельского хозяйства с применением современных технологий и программных средств.В статье представлены результаты проектирования и реализации программного обеспечения (ПО) для решения задачи классификации сельскохозяйственных показателей на основе применения комплекса методов интеллектуального анализа данных и машинного обучения. В рамках проектной части работы описаны функциональные и нефункциональные требования к программному обеспечению, архитектура и структура проектируемой программы, технологии и программные средства реализации. Предложена укрупненная архитектура ПО, состоящая из двух частей: пользовательского приложения на языке программирования Java и ядра выполнения R-скриптов. В результате проектирования выделено пять модулей в структуре ПО: средства взаимодействия с данными, первичная обработка данных, классификация данных, автоматический подбор параметров алгоритмов и «интеллектуальный» модуль. В качестве средств реализации ПО предложено использовать стек технологий, а именно: язык статистических вычислений R для реализации методов анализа данных и язык Java для разработки графического пользовательского интерфейса для доступа к функциям анализа данных R.Также в статье приведено описание двух разработанных модулей программного обеспечения, а именно: модуля первичной обработки данных и модуля классификации данных. В модуле первичной обработки данных реализованы расчет основных числовых характеристик показателей, исследование законов распределения показателей на основе применения критериев согласия Шапиро-Уилка, Андерсона-Дарлинга, Крамера-фон Мизеса, Лиллиефорса, исследование взаимосвязей в данных с помощью методов корреляционного и дисперсионного анализов данных. В модуле классификации реализованы методы сэмплирования для решения проблемы несбалансированности данных, а также модели классификаторов: логистическая регрессия,наивный Байес, дискриминантный анализ, нейросетевой метод (персептрон), деревья решений, реализована возможность оценки точности получаемых моделей с помощью набора метрик. Приведен пример решения задачи классификации уровня засоренности участка с помощью нейронной сети (персептрона), точность классификации составила на тестовой выборке 0,73. The agricultural industry is currently experiencing a constant increase in the data obtained, the need for their quality processing and accurate calculations to support decision-making is increasing. Hence, the tasks related to the development of algorithms, methods and software for solving problems of analysis and processing of data in the field of agriculture using modern technologies and software are of particular relevance.The research paper provides the results of design and further implementation of software for agricultural indicators classification problem solving based on the complex application of data mining and machine learning methods. In the framework of the design part the functional and non-functional software requirements, the architecture and structure of the designed software, implementation technologies, and developing tools were included. The proposed large-scale software architecture consists of two parts: a user application based on the Java programming language and a kernel of R-scripts execution. The software design was defined to consist of five modules: data interaction tools, primary data processing, data analysis, automated selection of algorithm parameters, and «intelligent» module. To implement the software, it was proposed to use the technology stack: statistical computing language R for the realization of data analysis methods and Java to develop a graphical user interface to access the R data analysis functions.Another section provides a description of two developed software modules, namely: the module of primary data processing and the module of data classification. The module of primary data processing involves calculation of the main numerical features, the examination of the distribution laws based on the application of the Shapiro-Wilk, Anderson-Darling, Cramér-von Mises, Lilliefors consent criteria and tests, the analysis of relationships in the data using methods of correlation and variance analyses. The module of classification implemented methods of sampling to solve the problem of unbalanced data as well as models of classifiers: logistic regression, naive Bayes, discriminant analysis, neural network method (perceptron), decision trees. The ability to assess the accuracy of the obtained models using a set of metrics is realized. A case of solving the problem of classifying the level of crop infestation using a neural network (perceptron) is presented, the accuracy of classification was 0.73 on the test sample.
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Краева, Я. А., and М. Л. Цымблер. "The use of MPI and OpenMP technologies for subsequence similarity search in very long time series on a computer cluster system with nodes based on the Intel Xeon Phi Knights Landing many-core processor." Numerical Methods and Programming (Vychislitel'nye Metody i Programmirovanie), no. 1 (January 20, 2019): 29–44. http://dx.doi.org/10.26089/nummet.v20r104.
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В настоящее время поиск похожих подпоследовательностей требуется в широком спектре приложений интеллектуального анализа временных рядов: моделирование климата, финансовые прогнозы, медицинские исследования и др. В большинстве указанных приложений при поиске используется мера схожести Dynamic Time Warping (DTW), поскольку на сегодняшний день научное сообщество признает меру DTW одной из лучших для большинства предметных областей. Мера DTW имеет квадратичную вычислительную сложность относительно длины искомой подпоследовательности, в силу чего разработан ряд параллельных алгоритмов ее вычисления на устройствах FPGA и многоядерных ускорителях с архитектурами GPU и Intel MIC. В настоящей статье предлагается новый параллельный алгоритм для поиска похожих подпоследовательностей в сверхбольших временных рядах на кластерных системах с узлами на базе многоядерных процессоров Intel Xeon Phi поколения Knights Landing (KNL). Вычисления распараллеливаются на двух уровнях: на уровне всех узлов кластера - с помощью технологии MPI и в рамках одного узла кластера - с помощью технологии OpenMP. Алгоритм предполагает использование дополнительных структур данных и избыточных вычислений, позволяющих эффективно задействовать возможности векторизации вычислений на процессорных системах Phi KNL. Эксперименты, проведенные на синтетических и реальных наборах данных, показали хорошую масштабируемость алгоритма. Nowadays, the subsequence similarity search is required in a wide range of time series mining applications: climate modeling, financial forecasts, medical research, etc. In most of these applications, the Dynamic Time Warping (DTW) similarity measure is used, since DTW is empirically confirmed as one of the best similarity measures for the majority of subject domains. Since the DTW measure has a quadratic computational complexity with respect to the length of query subsequence, a number of parallel algorithms for various many-core architectures are developed, namely FPGA, GPU, and Intel MIC. In this paper we propose a new parallel algorithm for subsequence similarity search in very large time series on computer cluster systems with nodes based on Intel Xeon Phi Knights Landing (KNL) many-core processors. Computations are parallelized on two levels as follows: by MPI at the level of all cluster nodes and by OpenMP within a single cluster node. The algorithm involves additional data structures and redundant computations, which make it possible to efficiently use the capabilities of vector computations on Phi KNL. Experimental evaluation of the algorithm on real-world and synthetic datasets shows that the proposed algorithm is highly scalable.
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O., Vinnychuk, Vinnychuk I., and Biloskurskyy R. "CONCEPTUAL FUNDAMENTALS OF PRACTICAL APPLICATION OF BUSINESS ANALYSIS." Scientific Bulletin of Kherson State University. Series Economic Sciences, no. 45 (March 30, 2022): 69–75. http://dx.doi.org/10.32999/ksu2307-8030/2022-45-9.
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The article investigates and systematizes the existing approaches to the term "business analyst" as a process of processing and studying data using certain methods and converting data into new knowledge to improve the efficiency of the enterprise. Business intelligence is defined as a set of methods, technologies, systems, practices, methodologies and programs that analyze business data. This analysis allows the company to understand and analyze the market position and make timely management decisions. A review of modern foreign scientific publications on business analytics. Despite the significant number of publications, the topic of research on the application of business intelligence methods is relevant and needs further study. The components of business analytics are high-lighted: data visualization, data aggregation, data mining, identification of associations and sequences, forecasting, optimization. The main stages of business analytics are studied in detail: descriptive analytics, diagnostic analytics, forecast analytics, recommendation analytics. The classification of types and methods of business analytics is car-ried out. Huge amounts of data that characterize the external business environment and activities of the enterprise do not allow to analyze and build scenarios for decision-making without modern information technology. The use of information technology business intelligence is a prerequisite for business management. The availability of business intelligence software is further enhanced by cloud technologies and services. The main characteristics of the most common data visualization software products Tableau and Microsoft Power BI are analyzed. Tableau is a series of visualization and data processing products used to create business intelligence and visual reporting. Microsoft Power BI is a web set of business intelligence tools that features high-quality and fast data visualization. Further de-velopment of business intelligence tools is related to the concept of "Industry 4.0", which provides for the automatic generation and analysis of large data sets.Keywords: business analytics, information systems, information technology, data visualization, decision making. У статті досліджено та систематизовано підходи до терміна «бізнес-аналітика» як процесу обробки та вивчення даних за допомогою визначених методів і перетворення даних нанові знання для підвищення ефек-тивності діяльності підприємства. Проведено огляд сучасних закордонних наукових публікацій із бізнес-аналітики. Виокремлено компоненти бізнес-аналітики: візуалізація даних, агрегування даних, інтелектуальний аналіз даних, ідентифікація асоціацій та послідовностей, прогнозування, оптимізація. Детально досліджено основні етапи бізнес-аналітики: описова аналітика, діагностична аналітика, прогнозна аналітика, рекоменда-ційна аналітика. Проведено класифікацію типів та методів бізнес-аналітики. Проаналізовано основні характеристики найпоширеніших програмних продуктів візуалізації даних Tableau та Microsoft Power BI.Ключовi слова: бізнес-аналітика, інформаційні системи, інформаційні технології, візуалізація даних, прийняття рішень.
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Цымблер, М. Л., and А. И. Гоглачев. "Discovery of typical subsequences of time series on graphical processor." Numerical Methods and Programming (Vychislitel'nye Metody i Programmirovanie), no. 4 (November 3, 2021): 344–59. http://dx.doi.org/10.26089/nummet.v22r423.
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Поиск типичных подпоследовательностей временного ряда является одной из актуальных задач интеллектуального анализа временных рядов. Данная задача предполагает нахождение набора подпоследовательностей временного ряда, которые адекватно отражают течение процесса или явления, задаваемого этим рядом. Поиск типичных подпоследовательностей дает возможность резюмировать и визуализировать большие временные ряды в широком спектре приложений: мониторинг технического состояния сложных машин и механизмов, интеллектуальное управление системами жизнеобеспечения, мониторинг показателей функциональной диагностики организма человека и др. Предложенная недавно концепция сниппета формализует типичную подпоследовательность временного ряда следующим образом. Сниппет представляет собой подпоследовательность, на которую похожи многие другие подпоследовательности данного ряда в смысле специализированной меры схожести, основанной на евклидовом расстоянии. Поиск типичных подпоследовательностей с помощью сниппетов показывает адекватные результаты для временных рядов из широкого спектра предметных областей, однако соответствующий алгоритм имеет высокую вычислительную сложность. В настоящей работе предложен новый параллельный алгоритм поиска сниппетов во временном ряде на графическом ускорителе. Распараллеливание выполнено с помощью технологии программирования CUDA. Разработаны структуры данных, позволяющие эффективно распараллелить вычисления на графическом процессоре. Представлены результаты вычислительных экспериментов, подтверждающих высокую производительность разработанного алгоритма. Discovery of typical subsequences in a time series is one of the topical problems of time series mining. In this problem, we are to find a set of subsequences that adequately represents the specified time series. The solution of such a problem makes it possible to summarize and visualize a large time series in a wide range of applications: monitoring of the technical condition of complex machines and mechanisms, intelligent management of life support systems, monitoring of indicators of functional diagnostics of the human body, etc. The recently proposed snippet concept formalizes a typical time series subsequence as follows. A snippet of a time series is a subsequence that many other subsequences of the given series are similar to, with respect to a specialized similarity measure based on the Euclidean distance. Despite the snippets discovery algorithm shows adequate results for time series from a wide range of subject domains, it has a high computational complexity. In this article, we propose a novel parallel algorithm for snippets discovery on GPU. Parallelization is performed through the CUDA programming technology. We developed data structures that allow for efficient parallelization of GPU calculations. The experimental results show the high performance of the proposed algorithm.
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Матвиенко, Ю. В., В. В. Костенко, А. Ф. Щербатюк, and А. В. Ремезков. "DEVELOPMENT OF THE TECHNOLOGICAL POTENTIAL OF AUTONOMOUS UNDERWATER VEHICLES." Podvodnye issledovaniia i robototehnika, no. 4(34) (January 24, 2020): 4–14. http://dx.doi.org/10.37102/24094609.2020.34.4.001.
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Перспективы создания подводных роботов – автономных и телеуправляемых необитаемых подводных аппаратов (АНПА, ТНПА) нового поколения связаны с разработкой технологий гибридных необитаемых подводных аппаратов (ГНПА), в которых интегрированы функции АНПА и ТНПА. Проблема состоит в значительном расширении технологических возможностей АНПА за счет оснащения их новыми инструментами, совершенствования систем бортового управления, вовлечения оператора в технологический процесс для оперативного контроля хода работ, порядка и условий выполнения принципиально новых технологических операций. ГНПА может выполнять широкий спектр бесконтактных работ, выходить к объекту обследования в соответствии с заданной программой, выполнять действия, связанные с формированием канала информационного обмена с постом управления, и далее выполнять контактные операции в супервизорном режиме. Первоочередные задачи создания гибридных аппаратов состоят в развитии функциональных свойств АНПА, включая: интеллектуализацию системы бортового управления, организацию супервизорного управления с включением оператора в процесс управления, расширение инструментального оснащения и оптимизацию конструктивных решений, организацию сетевых средств подводной навигации, организацию инфраструктуры подводного базирования аппарата при выполнении длительных работ по обслуживанию подводных добычных комплексов. В работе показана принципиальная возможность создания ГНПА на основе робототехнических комплексов и их систем, созданных в ИПМТ ДВО РАН за последние годы. Prospects of designing autonomous and remotely operated underwater vehicles (AUV and ROV) of the new generation rely on developing hybrid autonomous and remotely-operated vehicles (ARV), which combine functions of AUV and ROV. It is necessary to expanse significantly AUV's technological capabilities by equipping it with new instruments, upgrading onboard control systems, involving operators in the technological process for real-time control of work progress, and execution order and conditions of novel technological operations. ARV is capable of performing a wide specter of contactless operations: approach the target of research according to the stated program, perform operations related to establishing a data exchange channel with control station, and then carry out contact operation in supervisory mode. Priority tasks of hybrid vehicles designing consist of the development of AUV's functional properties, including: intellectualization of onboard control systems; provision of supervisory control involving an operator in control flow; expansion of instrumentation and optimization of structural solutions; providing a network means for underwater navigation; providing an infrastructure for underwater deployment while carrying out long-term missions on the maintenance of underwater mining complexes. Work demonstrates a principal achievability of designing an ARV based on robotic complexes and their systems developed in the IMTP FEB RAS for the past years.
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Gerasimenko, Olga A., and Ayman M. Kazybayeva. "Geodata mining – a technology of intellectual analysis of spatial data." Research result. Economic Research 7, no. 1 (March 30, 2021). http://dx.doi.org/10.18413/2409-1634-2021-7-1-0-8.
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Булдакова, Т. И., and А. Ш. Джалолов. "Choice of the Data Mining technologies for intrusion detection systems into a corporate network." Engineering Journal: Science and Innovation, no. 24 (November 2013). http://dx.doi.org/10.18698/2308-6033-2013-11-987.
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Жигайло, О. М. "ВИКОРИСТАННЯ ТЕХНОЛОГІЇ DATA MINING В АВТОМАТИЗОВАНІЙ СИСТЕМІ ПРОСТЕЖУВАННОСТІ ВИРОБНИЦТВА СИРОЇ СОНЯШНИКОВОЇ ОЛІЇ." Automation Technological and Business - Processes 19, no. 19 (October 9, 2014). http://dx.doi.org/10.15673/2312-3125.19/2014.27953.
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Martseniuk, V. P., V. V. Franchuk, A. S. Sverstiuk, and O. V. Franchuk. "ВИКОРИСТАННЯ ТЕХНОЛОГІЇ DATA MINING ДЛЯ З'ЯСУВАННЯ СУДОВО-МЕДИЧНИХ ЕКСПЕРТНИХ ОСОБЛИВОСТЕЙ НЕНАЛЕЖНОЇ МЕДИЧНОЇ ДОПОМОГИ." Medical Informatics and Engineering, no. 3 (October 22, 2018). http://dx.doi.org/10.11603/mie.1996-1960.2018.3.9463.
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У роботі представлені можливості технології штучного інтелекту Data Mining, зокрема методу індукції дерев рішень, для вирішення спеціальних питань під час судово-медичної експертизи кримінальних проваджень, відкритих проти лікарів у випадках неналежного надання медичної допомоги. На підставі отриманих результатів, обґрунтованих автоматизованою математичною програмою інтелектуальної обробки бази даних, встановлені конкретні судово-медичні експертні особливості неналежної медичної допомоги на прикладі кримінальних справ, порушених проти лікарів-терапевтів.
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Martsenyuk, V. P., and O. O. Stakhanska. "ПРО КЛІНІЧНУ ЕКСПЕРТНУ СИСТЕМУ, ЩО ГРУНТУЄТЬСЯ НА ПРАВИЛАХ, НА ОСНОВІ ТЕХНОЛОГІ DATA MINING." Medical Informatics and Engineering, no. 1 (May 13, 2015). http://dx.doi.org/10.11603/mie.1996-1960.2014.1.3788.
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In the work the topics of software implementation of rule induction method based on sequential covering algorithm are considered. Such approach allows us to develop clinical decision support system. The project is implemented within Netbeans IDE based on Java-classes.
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Kvyatkovskaya, Anastasia Evgenievna, Anna Olegovna Polumordvinova, Irina Yurievna Kvyatkovskaya, and Elena Vitalievna Chertina. "INFORMATION TECHNOLOGY OF SEARCHING COMPARATIVE COMPANIES FOR BUSINESS VALUATION USING INTELLIGENT AGENTS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics, January 25, 2019, 99–106. http://dx.doi.org/10.24143/2072-9502-2019-1-99-106.
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The paper deals with developing information technology of data processing for solving business valuation problems based on the selection of comparative companies. An emerging IT company or a startup are taken as the object of study, for which traditional valuation methods are not apt. In terms of the research task there has been introduced the concept of a precedent - a company for which the search of analogues is being realized. The basic concepts of multi-agent systems are used. Four types of intelligent agents are presented that provide the implementation of the elements of the end-to-end technology: information search of objects with specified properties, intelligent processing of user requests, monitoring of objects, data mining. Stage sequence of the distributed decision-making technology has been considered. There are given metric and non-metric information processing mechanisms about analogues using metrics and proximity measures. The problem of non-metric information processing has been formulated. The tasks of data mining analysis have been defined, which are vital for monitoring the IT-companies in order to evaluate the business. The presented conclusions are summarized in the form of a complex information technology of data processing.
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Martsenyuk, V. P., L. S. Babinets, and Yu V. Dronyak. "ВИКОРИСТАННЯ ТЕХНОЛОГІЇ DATA MINING ІЗ МЕТОЮ ДИФЕРЕНЦІАЛЬНОЇ ДІАГНОСТИКИ КОМОРБІДНИХ СТАНІВ ХРОНІЧНОГО ПАНКРЕАТИТУ Й АСКАРИДОЗУ НА ПІДСТАВІ ДАНИХ КЛІНІЧНОЇ СИМПТОМАТИКИ Й УЛЬТРАЗВУКОВИХ ДОСЛІДЖЕНЬ." Medical Informatics and Engineering, no. 4 (February 20, 2018). http://dx.doi.org/10.11603/mie.1996-1960.2017.4.8447.
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For diagnostics of chronic pancreatitis and ascaridosis comorbidity methodology of decision tree construction based on C5.0 algorithm is used. Data of both clinical symptomatology and ultrasonography can be applied. For each of types of researches and also for their totality a separate decision tree is built. The error of algorithm is investigated.
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Chekh, Nataliia, Olena Konoplina, and Yuliya Mizik. "INFORMATION TECHNOLOGIES IN ACCOUNTING AND RELATED SECURITY RISKS." Market Infrastructure, no. 55 (2021). http://dx.doi.org/10.32843/infrastruct55-31.
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Today, the business environment has become extremely dynamic due to rapid changes in information technology due to competition and the desire for efficiency. Designed to meet a wide range of economic requirements, new technologies offer flexibility, economies of scale, mobility and greater accuracy. The field of accounting is subject to this new era of change. The era of the Internet of Everything (IoE) is reshaping the profession of accountant according to the current needs of organizations. Artificial intelligence and process automation take on redundant and repetitive tasks performed by professionals, creating space for more complex activities such as analysis and business consulting. The article considers the main modern information technologies and the possibilities of their use in accounting. With the use of information technology, more opportunities have opened up in the field of accounting. The purpose of the article is to analyze the use of modern information technology in accounting, to study the features of their implementation and related risks for the company. Technological determinants of the development of the organization of accounting are: the spread of mobile communications; improving the provision of Internet access services; software development; conversion of smartphones, tablets into integrated devices, their active use in the workplace of accounting staff.The main advantages of such technologies as cloud computing platforms, big data, data mining and mobile technologies are identified. The main threats associated with the use of these technologies have also been identified. It is determined that new technologies, as well as the need for real-time reporting make changes in the profession of accountant. Novice accountants may lack the knowledge to efficiently obtain and process large amounts of data. This is due to the fact that the existing curricula of accounting faculties in Ukraine are not sufficiently focused on new technologies, such as cloud computing, Big Data or data mining. As a result, it can be difficult for accountants to secure confidential information using the latest technology.
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Кенджакын, А., and М. К. Малгаждарова. "Role of digital technologies in the life of society." INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES, no. 4(4) (August 11, 2020). http://dx.doi.org/10.54309/ijict.2020.4.4.003.
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В статье сделан обзор информации на тему цифровизации. Приведены официальные данные по итогам реализации ПРОГРАММЫ«ЦИФРОВОЙ КАЗАХСТАН» ЗА 2019годи примеры применения цифровых технологий в жизни граждан. В 2019 году в рамках реализации мероприятий госпрограммы «Цифровой Казахстан» было создано 8 тыс. рабочих мест. Совокупный экономический эффект от Программы за 2018 и 2019 годы превысил 600 млрд. тг. Значительные успехи достигнуты во внедрении цифровых технологий в сферы оказания государственных услуг, образования, здравоохранения, финансовый, транспортный и горно-металлургический секторы. The article provides an overview of information on the topic of digitalization. The official data on the results of the implementation of the Digital Kazakhstan program for 2019 and examples of the use of digital technologies in the lives of citizens are presented. In 2019, as part of the implementation of the activities of the state program "Digital Kazakhstan", 8 thousand jobs were created. The total economic effect from the Program for 2018 and 2019 exceeded 600 billion tenge. Significant progress has been achieved in the implementation of digital technologies in the provision of public services, education, health care, financial, transport and mining and metallurgical sectors.
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Zhadko, Kostiantyn, Tetiana Nosova, and Yuliia Horiashchenko. "PROBLEMS OF IMPLEMENTATION OF ADVANCED WORLD TECHNOLOGIES IN THE CONDITION OF DIGITAL BUSINESS." Scientific opinion: Economics and Management, no. 1(77) (2022). http://dx.doi.org/10.32836/2521-666x/2022-77-7.
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A study of potential opportunities and risks of blockchain implementation for Ukrainian enterprises was conducted. Proposals for the development of a system of actions for business tokenization have been developed. The ontological and organizational principles of the blockchain in the crypto industry are studied. The use of blockchain in the crypto industry as the main sphere of technology life is stated. The experience of application of blockchain technology of the United States of America and Great Britain is studied. The timeline projects of Ukrainian ministries and some state institutions, in particular the National Bank of Ukraine; on the introduction of advanced world technologies are analyzed. The impact of the introduction of blockchain technology on Ukrainian enterprises is described. Key barriers to blockchain-based technology development at Ukrainian enterprises have been identified, including: low bandwidth; significant delay time; bandwidth size and width; security issues; energy consuming bitcoin mining. The advantages of blockchain technology for business in various fields of activity are identified. A parallel was drawn between the activities of the largest public companies, the largest companies by market capitalization and startups with the highest rating in the world. The issues of normative-legal and institutional support of this problem in Ukraine and abroad were studied separately. Proposals for Ukrainian business are given, among which: to systematize the basic concepts related to cryptotechnologies; create a register of cryptocurrencies, which will indicate the name and protocol of the cryptocurrency; the adoption at the official level of a moratorium on the regulation and restriction of the right to engage in business related to cryptocurrencies; improvement of legal support for legalization of mining in Ukraine, inclusion of this activity in the national classifier, i.e. creation of Classification of economic activities, which can be added to the activities of private individuals or LLCs, and which will relate to the use of blockchain technology, data processing and smart contracts in distributed registers.
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Andrienko, Valentina, and Natalia Zhuravleva. "INFORMATION TECHNOLOGIES OF SYSTEM ANALYSIS IN SOCIO-ECONOMIC SPACE." Pryazovskyi Economic Herald, no. 1(24) (2021). http://dx.doi.org/10.32840/2522-4263/2021-1-39.
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The article provides an analytical review of new information technologies that are most relevant and important for systems analysis and modeling in their historical development. The relevance of the topic is determined by the need to systematize knowledge in the field of information technologies and their application for effective management of socio-economic processes. Traditionally established and new information technologies used in the socio-economic space are considered at the substantive level: technologies of databases (DB) and database management systems (DBMS), automated systems (AS) and automated workstations (AWS), data warehouses and data mining; technologies of teamwork in the office, telecommunication technologies for accessing information remote from the user, technologies for using integrated application packages (PPP), neuro-mathematical and neuro-information technologies and networks, engineering, hypertext, etc. The purpose is considered and the main functions and capabilities of each technology are formulated. They also analyzed their impact on the processes of socio-economic development. The examples of effective use of information technologies in various socio-economic spheres: financial, management, services of trade enterprises, commercial and government organizations are given. The interaction of new information technologies with artificial intelligence methods in the context of globalization is shown, as a result of which they become the main factor that changes the traditional decision-making criteria and the possibilities of world business (pricing, costs, location, etc.). In conclusion, the trends in the development of information technology of activity are listed. The main trend is the formation of a market for new information technologies, consisting of the main segments: private consumption (entertainment, personal services, etc.); business support (production, sales, marketing, etc.); intellectual professional work (automatic formalization of professional knowledge, etc.). Thus, the analysis showed that information technology is becoming a major factor in globalization, changing the traditional decision-making criteria and opportunities for global business.
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Голик, В. И., О. Г. Бурдзиева, Б. В. Дзеранов, and Х. О. Чотчаев. "Ground geodynamics control by regulating stress level." Геология и геофизика Юга России, no. 2() (June 27, 2020). http://dx.doi.org/10.46698/vnc.2020.93.21.011.
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Актуальность проблемы комплексного освоения и сохранения недр в настоящее время повышается необходимостью совершенствования основанных на новых принципах технологических процессов, что объясняет необходимость разработки новых и модернизации известных методов управления геодинамическими явлениями в массиве. Объектом исследования являются скальные сложно-структурные месторождения Садонской группы Центрального Кавказа, разработка которых увеличивает напряжения в рудовмещающих массивах с ухудшением качественных показателей использования недр и делает необходимым учет технологических воздействий на массив и меры геомеханического мониторинга его состояния. Целью исследования является обоснование возможности и целесообразности использования продуктов горного и обогатительного передела руд и изготовленных на их основе после извлечения из них полезных компонентов закладочных смесей. Методы достижения поставленной цели исследования включают в себя систематизацию и ранжирование связанных с управлением массивом геологических, технологических и экономических данных, разработку критериев оптимальности и формирование концепции ресурсосберегающей технологии разработки месторождений. Результаты. Детализирована концепция управления геомеханикой рудовмещающих массивов. Дано условие прочности массива на различных стадиях разработки месторождения. Предложена математическая модель взаимодействия переменных факторов. Сформулирован механизм сочетания традиционной технологии с открытым выработанным пространством и новой технологии с выщелачиванием металлов, как в блоках, так и в дезинтеграторах. Даны результаты оценки возможности использования хвостов обогащения в качестве сырья для изготовления твердеющих смесей, полученные в ходе полнофакторных исследований по программам государственных грантов. Даны сведения о гидрохимических способах получения металлов на рудниках. Вмещающим породам Садонских месторождений характерно перераспределение напряжений, в том числе, в геодинамическом режиме. Управление геодинамикой рудовмещающих пород путем регулирования величины напряжений в рудовмещающих массивах требует использования искусственных массивов из хвостов технологических процессов. Показано, что отработка вовлекаемых в производство некондиционных руд и хвостов обогащения запасов и доработка имеющихся запасов по комбинированной схеме может быть рентабельной Relevance of the problem of integrated development and conservation of mineral resources is currently increasing by the need to improve technological processes based on new principles, which explains the need to develop new and modernize well-known methods for managing geodynamic phenomena in the massif. Aim.The object of the study is the rock complex structural deposits of the Sadon group of the Central Caucasus, the development of which increases stresses in ore-bearing massifs with a deterioration in the quality of subsoil use and makes it necessary to take into account technological impacts on the massif and measures of geomechanical monitoring of its condition. The aim of the study is to substantiate the feasibility and advisability of using the products of mining and concentration processing of ores and made on their basis after extracting from them the useful components of filling mixtures. Methods to achieve the research goal include systematization and ranking of geological, technological and economic data related to managing an array of data, development of optimality criteria and the formation of a concept for resource-saving technology for field development. Results. The concept of managing the geomechanics of ore-bearing arrays is detailed. The condition of the array strength at various stages of field development is given. A mathematical model of the interaction of variable factors is proposed. The mechanism of combining traditional technology with open mined space and a new technology with leaching of metals, both in blocks and in disintegrators, is formulated. The results of evaluating the possibility of using enrichment tailings as raw materials for the manufacture of hardening mixtures, obtained in the course of full-factor studies on state grant programs. Information is given on hydrochemical methods for producing metals in mines. The host rocks of the Sadon deposits are characterized by a redistribution of stresses, including in the geodynamic regime. Management of the geodynamics of ore-bearing rocks by regulating the magnitude of stresses in ore-bearing massifs requires the use of artificial arrays from the tailings of technological processes. It is shown that the mining of substandard ores and tailings from the enrichment of reserves involved in the production and the refinement of existing reserves using a combined scheme can be cost-effective
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Rakhmetulayeva, S. B., and A. K. Kulbayeva. "SYMPTOMATIC ASSESSMENT OF DISEASES USING DECISION TREES AND ANALYSIS OF ELECTRONIC MEDICAL RECORDS." INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES, no. 1(9) (April 25, 2022). http://dx.doi.org/10.54309/ijict.2022.9.1.009.
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Supervised machine learning algorithms have emerged as the primary data mining tool. The use of health data to diagnose disease has lately revealed the potential use of these technologies. The purpose of this research is to find various forms of regulated machine learning algorithms as well as major trends in measuring performance and illness risk. In this article, we will attempt to anticipate patient illnesses based on their symptoms. We employ the decision tree algorithm to reach this aim, which will aid in the diagnosis of patients' health. The data set includes physiological measures for 42 different illnesses (diseases) and 129 different features (symptoms). We created a categorized decision tree model that uses standardization techniques known as format reduction to generalize data and delivers training to a dataset in a short amount of time. Developed trained models are then utilized to forecast illnesses, including their causes and preventative strategies, after they have been normalized. Контролируемые алгоритмы машинного обучения стали основным инструментом для извлечения данных. Использование медицинских данных для диагностики заболеваний недавно выявило возможное применение этих технологий. Цель данного исследования состоит в том, чтобы найти различные формы регулируемых алгоритмов машинного обучения, а также основные тенденции в измерении производительности и риска заболеваний. В этой статье мы попытаемся предсказать заболевания пациентов на основе их симптомов. Для достижения поставленной цели мы используем алгоритм решений, который помогает диагностировать здоровье пациентов. Набор данных включает физиологические показатели 42 различных заболеваний и 129 различных симптомов. Мы разработали классифицированную модель дерева решений, которая использует методы стандартизации, называемые сокращением форматов, для обобщения данных и обеспечивает обучение набору данных в короткие сроки. Затем наши обученные модели используются для прогнозирования заболеваний, включая их причины и стратегии профилактики, после нормализации.
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Акашев, Р. Д., Д. А. Хамитова, Н. К. Кадирова, R. Akashev, D. Khamitova, and N. Kadirova. "ANALYSIS OF THE APPLICATION OF FINANCIAL INSTRUMENTS BASED ON MONITORING AND EVALUATION OF INDUSTRIAL COMPANIES." Вестник Казахского университета экономики, финансов и международной торговли, no. 4(45) (February 10, 2022). http://dx.doi.org/10.52260/2304-7216.2021.4(45).36.
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В статье исследованы анализ применения финансовых инструментов на основе мониторинга и оценки деятельности промышленных компаний Республики Казахстан. На основе опыта и анализа зарубежных и казахстанских ученых, были рассмотрены вопросы прогнозирования устойчивого развития на основе моделей и факторов устойчивого экономического развития. Для определения степени использования финансовых инструментов предприятиями были использованы статистические данные промышленных компаний за 2015-2020 годы, и рассчитаны ключевые показатели, иллюстрирующие вовлеченность предприятий в инструменты, характеризующие финансовую состоятельность. С помощью регрессионного анализа проанализировано влияние представленных показателей финансово-хозяйственной деятельности предприятий горнодобывающей промышленности и разработки карьерови обрабатывающей промышленностина получаемую ими прибыль, в результате которого были сделаны выводы. Анализ сравнения двух рассматриваемых отраслей промышленности показал значительную разницу между формированием прибыли за счет увеличения дохода, свидетельствующий о более эффективном управлении расходами в горнодобывающей промышленности и разработке карьеров по сравнению с обрабатывающей промышленностью, что свидетельствует о применении инновационных методах и технологиях в промышленности, а также служит конкурентным преимуществом для роста и расширения компаний The article explored the analysis of the application of financial instruments based on monitoring and evaluation of industrial companies in the Republic of Kazakhstan. Based on the experience and analysis of foreign and Kazakh scientists, the issues of forecasting sustainable development based on models and factors of sustainable economic development were considered. To determine the extent to which enterprises use financial instruments, statistical data from industrial companies for 2015-2020 were used, and key indicators illustrating the involvement of enterprises in instruments that characterize financial solvency were calculated. Regression analysis was used to analyze the impact of the presented indicators of financial and economic activity of enterprises in the mining and quarrying and manufacturing industries on the profits they receive, which led to conclusions. The analysis of comparison of the two industries under consideration showed a significant difference between the formation of profit by increasing income, indicating a more effective cost management in mining and quarrying compared to the manufacturing industry, which indicates the use of innovative methods and technologies in the industry, and also serves as a competitive advantage for the growth and expansion of companies.