Academic literature on the topic 'Зустрічне навчання'
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Journal articles on the topic "Зустрічне навчання"
Стрілецька, Наталія, and Юлія Чеботар. "ФОРМУВАННЯ ЕЛЕМЕНТІВ КУЛЬТУРИ ДЕМОКРАТІЇ МОЛОДШИХ ШКОЛЯРІВ У ПРОЦЕСІ ПРОВЕДЕННЯ РАНКОВИХ ЗУСТРІЧЕЙ." Молодий вчений, no. 11 (99) (November 30, 2021): 185–92. http://dx.doi.org/10.32839/2304-5809/2021-11-99-42.
Full textСерьогіна, І. Ю. "ФОРМУВАННЯ САМООРГАНІЗАЦІЇ НАВЧАЛЬНОЇ ДІЯЛЬНОСТІ СТУДЕНТІВ ВНЗ." Educational Dimension 30 (May 19, 2022): 118–23. http://dx.doi.org/10.31812/educdim.4818.
Full textКачак, Тетяна Богданівна. "ЦИФРОВІ ІНСТРУМЕНТИ ЛІТЕРАТУРНОЇ ОСВІТИ МАЙБУТНІХ УЧИТЕЛІВ ПОЧАТКОВОЇ ШКОЛИ В УМОВАХ ДИСТАНЦІЙНОГО НАВЧАННЯ." Information Technologies and Learning Tools 86, no. 6 (December 30, 2021): 144–69. http://dx.doi.org/10.33407/itlt.v86i6.4079.
Full textDoroshkevych, K. O., M. M. Voronovska, and I. Z. Salata. "Підходи до забезпечення менторингової діяльності на підприємствах." Scientific Bulletin of UNFU 29, no. 4 (April 25, 2019): 47–49. http://dx.doi.org/10.15421/40290409.
Full textПанасенко, Елліна, Софія Березка, and Вікторія Лічман. "КОЛАБОРАЦІЯ ТЕОРІЇ ТА ПРАКТИКИ У РАМКАХ ПІДГОТОВКИ МАЙБУТНІХ ПСИХОЛОГІВ ДО РОБОТИ В ІНКЛЮЗИВНІЙ ОСВІТІ." Вісник ХНПУ імені Г. С. Сковороди "Психология", no. 64 (2021): 179–92. http://dx.doi.org/10.34142/23129387.2021.64.11.
Full textРоманишин, Юлія Любомирівна. "ВЕБОРІЄНТОВАНІ ВІРТУАЛЬНІ СПІЛЬНОТИ ТА КОМУНІКАЦІЇ В НАВЧАННІ ФАХІВЦІВ ІНФОРМАЦІЙНОЇ СФЕРИ." Information Technologies and Learning Tools 85, no. 5 (November 1, 2021): 228–43. http://dx.doi.org/10.33407/itlt.v85i5.3850.
Full textКатіс, Крістос. "ІННОВАЦІЙНА ПРОГРАМА PROFLEC-CY ДЛЯ ПРОФЕСІЙНОГО РОЗВИТКУ ОСВІТНІХ ЛІДЕРІВ: РЕЗУЛЬТАТИ ОЦІНЮВАННЯ УЧАСНИКІВ." Social Work and Education 8, no. 1 (April 2, 2021): 106–15. http://dx.doi.org/10.25128/2520-6230.21.1.7.
Full textVoitovych, Iryna, Vasyl Voitovych, and Ninel Matskevych. "Рекреаційний туризм у процесі підготовки майбутніх фахівців галузі фізичної культури та здоров’я." Physical education, sports and health culture in modern society, no. 3 (43) (September 27, 2018): 3–11. http://dx.doi.org/10.29038/2220-7481-2018-03-03-11.
Full textГайтан, Олена Миколаївна. "ПОРІВНЯЛЬНИЙ АНАЛІЗ МОЖЛИВОСТЕЙ ВИКОРИСТАННЯ ІНСТРУМЕНТАРІЮ ВЕБІНАРОРІЄНТОВАНИХ ПЛАТФОРМ ZOOM, GOOGLE MEET ТА MICROSOFT TEAMS В ОНЛАЙН-НАВЧАННІ." Information Technologies and Learning Tools 87, no. 1 (March 1, 2022): 33–67. http://dx.doi.org/10.33407/itlt.v87i1.4441.
Full textГрицай, Наталя Ігорівна. "Інформаційні технології як засіб формування інтелектуальних умінь учнів початкової школи." New computer technology 5 (November 2, 2013): 26–27. http://dx.doi.org/10.55056/nocote.v5i1.61.
Full textDissertations / Theses on the topic "Зустрічне навчання"
Паржин, Юрій Володимирович. "Моделі і методи побудови архітектури і компонентів детекторних нейроморфних комп'ютерних систем." Thesis, НТУ "ХПІ", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/34755.
Full textDissertation for the degree of Doctor of Technical Sciences in the specialty 05.13.05 – Computer systems and components. – National Technical University "Kharkiv Polytechnic Institute", Ministry of Education and Science of Ukraine, Kharkiv, 2018. The thesis is devoted to solving the problem of increasing the efficiency of building and using neuromorphic computer systems (NCS) as a result of developing models for constructing their components and a general architecture, as well as methods for their training based on the formalized detection principle. As a result of the analysis and classification of the architecture and components of the NCS, it is established that the connectionist paradigm for constructing artificial neural networks underlies all neural network implementations. The detector principle of constructing the architecture of the NCS and its components was substantiated and formalized, which is an alternative to the connectionist paradigm. This principle is based on the property of the binding of the elements of the input signal vector and the corresponding weighting coefficients of the NCS. On the basis of the detector principle, multi-segment threshold information models for the components of the detector NCS (DNCS): block-detectors, block-analyzers and a novelty block were developed. As a result of the developed method of counter training, these components form concepts that determine the necessary and sufficient conditions for the formation of reactions. The method of counter training of DNCS allows reducing the time of its training in solving practical problems of image recognition up to one epoch and reducing the dimension of the training sample. In addition, this method allows to solve the problem of stability-plasticity of DNCS memory and the problem of its overfitting based on self-organization of a map of block-detectors of a secondary level of information processing under the control of a novelty block. As a result of the research, a model of the network architecture of DNCS was developed, which consists of two layers of neuromorphic components of the primary and secondary levels of information processing, and which reduces the number of necessary components of the system. To substantiate the increase in the efficiency of constructing and using the NCS on the basis of the detector principle, software models were developed for automated monitoring and analysis of the external electromagnetic environment, as well as recognition of the manuscript figures of the MNIST database. The results of the study of these systems confirmed the correctness of the theoretical provisions of the dissertation and the high efficiency of the developed models and methods.
Паржин, Юрій Володимирович. "Моделі і методи побудови архітектури і компонентів детекторних нейроморфних комп'ютерних систем." Thesis, НТУ "ХПІ", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/34756.
Full textDissertation for the degree of Doctor of Technical Sciences in the specialty 05.13.05 – Computer systems and components. – National Technical University "Kharkiv Polytechnic Institute", Ministry of Education and Science of Ukraine, Kharkiv, 2018. The thesis is devoted to solving the problem of increasing the efficiency of building and using neuromorphic computer systems (NCS) as a result of developing models for constructing their components and a general architecture, as well as methods for their training based on the formalized detection principle. As a result of the analysis and classification of the architecture and components of the NCS, it is established that the connectionist paradigm for constructing artificial neural networks underlies all neural network implementations. The detector principle of constructing the architecture of the NCS and its components was substantiated and formalized, which is an alternative to the connectionist paradigm. This principle is based on the property of the binding of the elements of the input signal vector and the corresponding weighting coefficients of the NCS. On the basis of the detector principle, multi-segment threshold information models for the components of the detector NCS (DNCS): block-detectors, block-analyzers and a novelty block were developed. As a result of the developed method of counter training, these components form concepts that determine the necessary and sufficient conditions for the formation of reactions. The method of counter training of DNCS allows reducing the time of its training in solving practical problems of image recognition up to one epoch and reducing the dimension of the training sample. In addition, this method allows to solve the problem of stability-plasticity of DNCS memory and the problem of its overfitting based on self-organization of a map of block-detectors of a secondary level of information processing under the control of a novelty block. As a result of the research, a model of the network architecture of DNCS was developed, which consists of two layers of neuromorphic components of the primary and secondary levels of information processing, and which reduces the number of necessary components of the system. To substantiate the increase in the efficiency of constructing and using the NCS on the basis of the detector principle, software models were developed for automated monitoring and analysis of the external electromagnetic environment, as well as recognition of the manuscript figures of the MNIST database. The results of the study of these systems confirmed the correctness of the theoretical provisions of the dissertation and the high efficiency of the developed models and methods.
Reports on the topic "Зустрічне навчання"
Великодна, Мар’яна Сергіївна, and Ірина Олександрівна Франкова. Психологічна та психотерапевтична допомога під час пандемії COVID-19: сучасні виклики. Психосоматична медицина та загальна практика, 2020. http://dx.doi.org/10.31812/123456789/3872.
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