17 research outputs found

    Machine learning technique for morphological classification of galaxies at z<0.1 from the SDSS

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    Methods. We used different galaxy classification techniques: human labeling, multi-photometry diagrams, Naive Bayes, Logistic Regression, Support Vector Machine, Random Forest, k-Nearest Neighbors, and k-fold validation. Results. We present results of a binary automated morphological classification of galaxies conducted by human labeling, multiphotometry, and supervised Machine Learning methods. We applied its to the sample of galaxies from the SDSS DR9 with redshifts of 0.02 < z < 0.1 and absolute stellar magnitudes of 24m < Mr < 19.4m. To study the classifier, we used absolute magnitudes: Mu, Mg, Mr , Mi, Mz, Mu-Mr , Mg-Mi, Mu-Mg, Mr-Mz, and inverse concentration index to the center R50/R90. Using the Support vector machine classifier and the data on color indices, absolute magnitudes, inverse concentration index of galaxies with visual morphological types, we were able to classify 316 031 galaxies from the SDSS DR9 with unknown morphological types. Conclusions. The methods of Support Vector Machine and Random Forest with Scikit-learn machine learning in Python provide the highest accuracy for the binary galaxy morphological classification: 96.4% correctly classified (96.1% early E and 96.9% late L types) and 95.5% correctly classified (96.7% early E and 92.8% late L types), respectively. Applying the Support Vector Machine for the sample of 316 031 galaxies from the SDSS DR9 at z < 0.1, we found 141 211 E and 174 820 L types among them.Comment: 10 pages, 5 figures. The presentation of these results was given during the EWASS-2017, Symposium "Astroinformatics: From Big Data to Understanding the Universe at Large". It is vailable through \url{http://space.asu.cas.cz/~ewass17-soc/Presentations/S14/Dobrycheva_987.pdf

    Digitalization as a New Paradigm for Managing the Development of Tourism in Ukraine in the Post-War Period

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    The article, based on the analysis of the main trends in the development of the tourism market in the context of global digitalization, which has intensified in the field of tourism and hospitality, substantiates structural changes in the tourist services market of Ukraine. The subject of the study is the introduction of digital technologies in the tourism industry of Ukraine in the post-war period. The purpose of the article is to study the features of the use of digital technologies in the tourism industry of Ukraine. The achievement of this goal was facilitated by the solution of the following tasks: to explore various forms of digitalization in the tourism industry of Ukraine; to offer an improved conception of managing the development of tourism in Ukraine in the post-war period. The article used methods of analysis and synthesis to summarize the development of digital technologies in tourism; method of comparative analysis – to compare the experience of international and national digital tourism development; prognostic methods – to outline the prospects for further development of digital tourism in Ukraine in the post-war period. The authors made an attempt to predict the prospects for digitalization of the tourism industry of our country based on the integration of several defining areas – AR (augmented reality), VR (virtual reality), AI (artificial intelligence), as well as robots and blockchain technologies. The article quite fully covers the issues of digital support of business processes in the field of tourism, analyzes the opportunities and prospects of tourism BigData, which are used for analyzing information, making forecasts, sustainable developing the tourism industry. The deliberate implementation of best practices in the field of digital technologies can help our country’s tourism industry implement strategies that become possible by the wider use of digital content and platforms. The provision of a modern business model will help stabilize the working environment in the post-war period, while stimulating an innovative approach in the field of tourism

    Use of anticoagulants and antiplatelet agents in stable outpatients with coronary artery disease and atrial fibrillation. International CLARIFY registry

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    Modelling the phase synchronization in systems of two and three coupled oscillators

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    We obtain regions of synchronization of two and three globally coupled oscillators, and describe the main mechanisms and bifurcaations through which the system synchronization is los

    Автоматизована система освітлення в житлових приміщеннях

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    This work is devoted to the automation of residential buildings lighting systems. Analysis of existing lighting systems was held to find the ways of further improvement. A structure of proposed system was developed. All the elements of the experimental installation, including drivers, photosensors, lighting fixtures, microcontroller, were chosen. Algorithm of system operation was created and software for microcontroller was designed. Proposed algorithm allows to take into account the reflective properties of interior elements and to provide the higher quality of lighting.Работа посвящена автоматизации систем освещения жилых домов. Был проведен анализ существующих систем освещения с целью поиска путей их дальнейшего совершенствования. Была разработана структура предложенной системы. Были выбраны все элементы экспериментальной установки, включая драйверы, фотосенсоры, осветительные приборы, микроконтроллер. Создан алгоритм работы системы и разработано программное обеспечение для микроконтроллера. Предложенный алгоритм позволяет учитывать светоотражающие свойства элементов интерьера и обеспечивать более высокое качество освещения.Роботу присвячено автоматизації систем освітлення житлових будинків. Проведено аналіз існуючих систем освітлення з метою пошуку шляхів їх подальшого вдосконалення. Розроблено структуру запропонованої системи. Були обрані всі елементи експериментальної установки, включаючи драйвери, фотосенсори, освітлювальні прилади, мікроконтролер. Створено алгоритм роботи системи та розроблено програмне забезпечення для мікроконтролера. Запропонований алгоритм дозволяє враховувати світловідбиваючі властивості елементів інтер’єру та забезпечувати більш високу якість освітленн

    THE EFFECT OF MONOCOT INTRONS ON TRANSGENE EXPRESSION IN Nicotiana GENUS PLANTS

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    The aim of the work was to study the effect of introns of the rice OsAct1 and the maize hsp70 genes on the transgene expression in Nicotiana plants in order to find out of their use in the testing of vectors containing these monocot introns. Next methods were used: Agrobacterium-mediated transformation of leaves of greenhouse N. benthamiana and N. tabacum plants by vector pCB271 containing the introns of cereals, light fluorescence microscopy and fluorimetry of GFP. The presence of transgenes was detected by polymerase chain reaction. The transient GFP expression was observed in infiltrated tissue of N. benthamiana. Transgenic plants of N. tabacum resistant to kanamycin were obtained. Fluorescence of GFP in extracts of some transgenic tobacco lines was shown. The impairment of the transgene expression in some N. tabacum transformants has been observed. So, transgenes, containing introns from the hsp70 corn or from the OsAct1 rice genes downstream the promotor, are expressed in Nicotiana plants. Thus, N. benthamiana and N. Tabacum plants can be used to test vectors constructs for cereals transformation. It has been shown that the monocot introns can have the negative impact on the transgene expression in Nicotiana plants

    Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02<z<0.1

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    We applied the image-based approach with a convolutional neural network model to the sample of low-redshifts galaxies with 24m<Mr<19.4m-24^{m}<M_{r}<-19.4^{m} from the SDSS DR9. We divided it into two subsamples, SDSS DR9 galaxy dataset and Galaxy Zoo 2 (GZ2) dataset, considering them as the inference and training datasets, respectively. As a result, we created the morphological catalog of 315782 galaxies at 0.02<z<0.1, where morphological five classes and 34 detailed features (bar, rings, number of spiral arms, mergers, etc.) were first defined for 216148 galaxies (inference dataset) by the image-based CNN classifier. For the rest of galaxies the initial morphological classification was re-assigned as in the GZ2 project. Our method shows the promising performance of morphological classification attaining more 93 % of accuracy for five classes morphology prediction except the cigar-shaped (75 %) and completely rounded (83 %) galaxies. Main results are presented in the catalog of 19468 completely rounded, 27321 rounded in-between, 3235 cigar-shaped, 4099 edge-on, 18615 spiral, and 72738 general low-redshift galaxies of the studied SDSS sample. As for the classification of galaxies by their detailed structural morphological features, our CNN model gives the accuracy in the range of 92-99 % depending on features, a number of galaxies with the given feature in the inference dataset, and the galaxy image quality. We demonstrate that implication of the CNN model with adversarial validation and adversarial image data augmentation improves classification of smaller and fainter SDSS galaxies with mrm_{r} <17.7.Comment: 25 pages, 7 figures, 2 table
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