Academic literature on the topic '004.8:004.93'
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Journal articles on the topic "004.8:004.93"
Burgaz, Sonia, Concepción García, María Gómez-Cañas, Alain Rolland, Eduardo Muñoz, and Javier Fernández-Ruiz. "Neuroprotection with the Cannabidiol Quinone Derivative VCE-004.8 (EHP-101) against 6-Hydroxydopamine in Cell and Murine Models of Parkinson’s Disease." Molecules 26, no. 11 (May 28, 2021): 3245. http://dx.doi.org/10.3390/molecules26113245.
Full textCaprioglio, Diego, Daiana Mattoteia, Orazio Taglialatela-Scafati, Eduardo Muñoz, and Giovanni Appendino. "Cannabinoquinones: Synthesis and Biological Profile." Biomolecules 11, no. 7 (July 5, 2021): 991. http://dx.doi.org/10.3390/biom11070991.
Full textGarcía-Martín, Adela, Martín Garrido-Rodríguez, Carmen Navarrete, Carmen del Río, María L. Bellido, Giovanni Appendino, Marco A. Calzado, and Eduardo Muñoz. "EHP-101, an oral formulation of the cannabidiol aminoquinone VCE-004.8, alleviates bleomycin-induced skin and lung fibrosis." Biochemical Pharmacology 157 (November 2018): 304–13. http://dx.doi.org/10.1016/j.bcp.2018.07.047.
Full textPalomares, Belen, Francisco Ruiz-Pino, Carmen Navarrete, Inmaculada Velasco, Miguel A. Sánchez-Garrido, Carla Jimenez-Jimenez, Carolina Pavicic, et al. "VCE-004.8, A Multitarget Cannabinoquinone, Attenuates Adipogenesis and Prevents Diet-Induced Obesity." Scientific Reports 8, no. 1 (October 31, 2018). http://dx.doi.org/10.1038/s41598-018-34259-0.
Full textNavarrete, Carmen, Francisco Carrillo-Salinas, Belén Palomares, Miriam Mecha, Carla Jiménez-Jiménez, Leyre Mestre, Ana Feliú, et al. "Hypoxia mimetic activity of VCE-004.8, a cannabidiol quinone derivative: implications for multiple sclerosis therapy." Journal of Neuroinflammation 15, no. 1 (March 1, 2018). http://dx.doi.org/10.1186/s12974-018-1103-y.
Full textdel Río, Carmen, Carmen Navarrete, Juan A. Collado, M. Luz Bellido, María Gómez-Cañas, M. Ruth Pazos, Javier Fernández-Ruiz, et al. "The cannabinoid quinol VCE-004.8 alleviates bleomycin-induced scleroderma and exerts potent antifibrotic effects through peroxisome proliferator-activated receptor-γ and CB2 pathways." Scientific Reports 6, no. 1 (February 18, 2016). http://dx.doi.org/10.1038/srep21703.
Full textDissertations / Theses on the topic "004.8:004.93"
Шихутський, Сергій Олександрович. "Автоматизована система контролю розрахунків для мережі магазинів роздрібної торгівлі." Master's thesis, КПІ ім. Ігоря Сікорського, 2019. https://ela.kpi.ua/handle/123456789/32286.
Full textThe object of the study is a complex of distributed data processing systems in the overall retail ecosystem and design of self-service systems within the selected ecosystem. Research methods - abstraction method, analysis and synthesis, induction and deduction, comparison method, modeling method. The equipment used in the study is a personal computer. Self-service technology using self-scanning on a mobile platform is an innovative approach in the retail trade. The dissertation elaborates the detailed architecture of the future system, describes all interactions between its elements of the system, as well as substantiates the choice of tools to be used in the development.
Смажелюк, Микола Вадимович. "Дослідження методів інтерполяції на візуальному полі уваги." Thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2017. http://elartu.tntu.edu.ua/handle/123456789/18971.
Full textТопчієв, Борис Сергійович. "Алгоритмічно-програмний метод колоризації зображень." Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/33832.
Full textThis master's dissertation is devoted to the research and development of an algorithmic-software method of coloring images using neural networks. This master's dissertation includes research on the problem of image colorization, self-developed algorithmic-software method for semi-automatic image colorization with the participation of a user who makes their own color prompts. In order to test and demonstrate the work of the developed neural network system, a simple web service was created, which allows the user to select the desired image, use the color palette to enter their own tips and get the result of the system. This master's dissertation provides a detailed analysis of existing problems in working with images, a review of various algorithms for eliminating defects in images and proposed its own method for performing interactive coloring of images with the participation of the user. A simple web service has also been developed, which deploys trained models for their operation.
Рекеда, Володимир Валерійович. "Вебсервіс підвищення роздільної здатності зображень з використанням SR-алгоритмів." Master's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/45914.
Full textActuality of theme. The task of improving image resolution is important for various practical applications. Such applications include the processing and analysis of medical images, satellite photographs, data processing from video surveillance devices, etc. These applications require high image quality, so over the last two decades, many methods have been proposed to improve image resolution. To date, there are two main approaches used in solving this problem. The first way is hardware. To do this, you must use cameras with a high quality matrix. The disadvantage of this approach is the need to use expensive specialized equipment. Another way is to use software that implements various algorithms to improve image quality. Such algorithms are called SR algorithms that allow you to qualitatively increase the resolution of the original image, which goes beyond the physical resolution of the digital sensor that recorded the image. The advantage of this approach is to reduce the requirements for the hardware component. The object of research is the problem of increasing the resolution of the image with the initial low resolution. The subject of research are algorithms and means of increasing the resolution of images. The goal of the work: modification of the SR-algorithm and development on its basis of a web service to improve image resolution. The scientific novelty is as follows: a web service is proposed to increase the resolution of the image using SR-algorithms. This service has an open API. Modification "Super resolution from a single image" is used. A feature of this modification is that the low-resolution image is converted to a high-resolution image without any other additional input information. Practical value of the results obtained in this work is that the developed web service allows you to increase the resolution of the image without the use of additional input data. This functionality can be useful in many areas that require working with high-resolution images, such as medical, video surveillance, etc. Also developed web service has an open API that allows you to use it in other software. Approbation of work. The main provisions and results of the work were presented and discussed at the XIV scientific conference of undergraduates and graduate students "Applied Mathematics and Computing" PMK-2021 (Kyiv, November 17-19, 2021). An article was published at the conference "VIII International Scientific and Technical Internet Conference" Modern Methods, Information, Software and Technical Support of Management Systems of Organizational, Technical and Technological Complexes" (Kyiv, November 26, 2021). Structure and scope of work. The master's dissertation consists of an introduction, four chapters and conclusions. The introduction presents a general description of the work, assesses the current state of the problem, substantiates the relevance of research, formulates the purpose and objectives of research, shows the scientific novelty of the results and the practical value of the work, provides information on testing the results and their implementation. The first section discusses the existing software tools that increase the image resolution. The second section describes the principles of SR-algorithms and compares various modifications of SR-algorithms. The third section and the fourth sections provide the structure and description of the developed software, as well as testing and analysis of the results of the study. The conclusions present the results of the work. The work is presented on 81 sheets, contains references to the list of used literature sources.
Костомаха, Марія Володимирівна, and Mariia Kostomakha. "Комп’ютерна система біометричної аутентифікації особи за відбитком пальця." Bachelor's thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2021. http://elartu.tntu.edu.ua/handle/lib/35567.
Full textIn the qualification work, a computer system of biometric authentication of a person by fingerprint is designed, which meets the requirements of the technical task. The goal of the work was achieved through the use of sound hardware and developed software. The main hardware devices of the designed system are: fingerprint scanner based on ZFM-20; Raspberry PI Model B reading and authentication process control device; component for outputting information messages for interaction with the user LCD 2 * 16. The interaction between the fingerprint scanner and the Raspberry PI is provided by using a USB Serial adapter. The success of the authentication is additionally signaled by the LED. The logic of the software is implemented using Python programming language supported by the selected single-chip mini-computer.
ПЕРЕЛІК ОСНОВНИХ УМОВНИХ ПОЗНАЧЕНЬ, СИМВОЛІВ І СКОРОЧЕНЬ 8 ВСТУП 9 1 АНАЛІЗ ВИМОГ ТЕХНІЧНОГО ЗАВДАННЯ ТА МЕТОДІВ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ 10 1.1 Аналіз вимог технічного завдання на проектування комп’ютерної системи біометричної аутентифікації особи за відбитком пальця 10 1.2 Методи і засоби аутентифікації особи 16 2 РОЗРОБКА ПРОЕКТУ КОМП’ЮТЕРНОЇ СИСТЕМИ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ ЗА ВІДБИТКОМ ПАЛЬЦІВ 22 2.1 Архітектура комп’ютерної системи біометричної аутентифікації 22 2.2 Обґрунтування вибору та аналіз технічних характеристики Raspberry PI 24 2.3 Аналіз технічних характеристик сканера відбитків пальців 28 2.4 Особливості застосування LCD-дисплея 32 2.5 Перетворювач USB – UART 35 2.6 Побудова схеми комп’ютерної системи біометричної аутентифікації особи за відбитком пальця 36 3 ПРОГРАМНЕ ЗАБЕЗПЕЧЕННЯ КОМП’ЮТЕРНОЇ СИСТЕМИ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ ЗА ВІДБИТКОМ ПАЛЬЦІВ 41 3.1 Реалізація логіки роботи програмного забезпечення комп’ютерної системи біометричної аутентифікації 41 3.2 Тестування комп’ютерної системи аутентифікації особи 53 РОДІЛ 4 БЕЗПЕКА ЖИТТЄДІЯЛЬНОСТІ, ОСНОВИ ОХОРОНИ ПРАЦІ 56 4.1 Вплив виробничого середовища на працездатність та здоров'я користувачів комп'ютерів 56 4.2 Захист населення у надзвичайних ситуаціях від впливу радіації 59 ВИСНОВКИ 56 СПИСОК ВИКОРИСТАНИХ ДЖЕРЕЛ 57 Додаток A. Технічне завдання Додаток Б. Програмне забезпечення комп’ютерної системи біометричної аутентифікації особи за відбитком пальця
Петрик, Віталій Віталійович. "Розпізнавання поведінки лабораторних тварин у реальному часі." Master's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/41623.
Full textAutomated observation and analysis of animal behavior is an important part of research in neurology and pharmacology. Although deep learning models show high results in recognizing human actions, they are insufficiently studied in tasks of recognizing animal behavior due to the lack of dataset. In this work, we created our own dataset, consisting of 919 short clips, and investigated the modern model I3D and model R(2+1)D to solve the problem of recognizing mouse behavior. We achieved an accuracy of 96.3% and 95.8%, respectively. We also demonstrated the effect of two-stream fusion ratios on prediction perfomances. The results showed that the use of pre-trained models of deep learning can exceed the accuracy of models from previous studies.
Автоматизированное наблюдение и анализ поведения животных является важной частью исследований в области неврологии и фармакологии. Хотя модели глубокого обучения показывают высокие результаты в задачах распознавания действий человека, они недостаточно изучены при применении к задачам распознавания поведения животных из-за отсутствия необходимой выборки данных. В этой работе мы создали собственную выборку данных, состоящий из 919 коротких клипов, и исследовали современные модели I3D и модель R(2 +1)D для решения задачи распознавания поведения мыши. Мы достигли точности до 96.3% и 95.8% соответственно. Мы также продемонстрировали влияние коэффициентов слияния двух потоков моделей на точность прогнозов. Результаты показали, что использование предварительно натренированных моделей глубокого обучения может превзойти точность моделей из предыдущих исследований.
Шурук, Андрій Сергійович. "Система аналізу людської активності на основі даних з носимих пристроїв." Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/38278.
Full textThe urgency of the problem. Globalization and population growth are contributing to the development of areas related to human activity monitoring, and thus to the emergence of new tools for monitoring various human performance indicators and ways to analyze these indicators. Given these factors, it is important in today's world to properly use such volumes of data in market conditions. When it comes to, for example, caring for the elderly, it is important to properly analyze and try to recognize a particular human activity, it can help increase the life expectancy of the elderly. Relationship with working with scientific programs, plans, topics. Thesis of master's level of higher education was performed at the National Technical University of Ukraine "Kyiv Polytechnic Institute named after Igor Sikorsky" in accordance with the plans of research work of the Department of Computer Science. The purpose and objectives of the study. The aim of this work is to study the possibility of recognizing human activity based on the data of wearable devices. The aim is to develop a system built on a neural network capable of recognizing human activity and providing it to the user through a cross-platform application. Object of study. The process of recognizing human activity using elements of the neural network. Subject of study. Methods of analysis and processing of data obtained from wearable devices in real time. Novelty. A new method of recognizing human activity based on the data of wearable devices is proposed, which, due to the use of a neural network, allows to obtain real-time recognition results with high accuracy.
Бернацька, Дарина Леонідівна. "Штучний інтелект і психологія. чи може робот замінити психолога?" Thesis, Національний авіаційний університет, 2021. https://er.nau.edu.ua/handle/NAU/52239.
Full textГурбанов, Т. А. "Технології порівняльного аналізу електронних текстів як засіб боротьби з плагіатом." Thesis, Національний авіаційний університет, 2021. https://er.nau.edu.ua/handle/NAU/54371.
Full textЗ розвитком науки та технологій ми можемо отримати багато нових можливостей для доступу до знань, але при цьому розвиваються старі та створюються нові проблеми в галузі освіти. Технології, що дозволяють отримати блискавичний доступ до багатьох джерел інформації та наукових робіт є однією з причин гострої проблеми плагіату цих наукових робіт.
Новіченко, Неля Валеріївна. "Система розпізнавання архітектурних стилів будівель за зображеннями." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2019. https://ela.kpi.ua/handle/123456789/30980.
Full textStructure and scope of work. Diploma project consists of six sections, contains 18 drawings, 21 tables, 1 applications, 17 sources. The diploma project is devoted to the development of tasks for the classification of images in order to determine the architectural styles of the buildings. Automatic methods for the classification of images during the analysis of architectural objects solve the problem of documenting cultural heritage and significantly reduce mistakes in sorting: usually a large number of images are processed and this is a tedious task, the process of classification by experts is prone to errors and takes a lot of time. The correct classification allows to study and analyze cultural heritage more effectively. In the diploma project were considered methods of classification of digital images, based on machine learning with the help of neural networks. The section on information provision define the data for training neural network, input and output data to a set of tasks, requirements for images for analysis, which corresponds to the set objectives of the project. The section of mathematical support is devoted to substantiation of the chosen approach of training the system, which allows to increase the accuracy of the results. The software section describes the main tools for developing a set of tasks, the requirements for technical support. This section defines and justifies the software architecture. The technology section describes the user's manual and tests a set of tasks.