Institute of Automation and Control Processes


The Institute of Automation and Control Processes with Computation Center of the Far Eastern Scientific Center, Siberian Branch of the USSR Academy of Sciences, was established on the 1st of June, 1971 on the base of the Department of Technical Cybernetics, Far Eastern Subsidiary, Siberian Branch, USSR Academy of Sciences by the Order of Presidium of USSR Academy of Sciences No 383, the 20th of May. 1971.

Today the Institute has Federal Institution Status and is incorporated into the Far Eastern Branch of the Russian Academy of Sciences. It occupies leading position in the field of physics and mathematics and technical sciences. The Institute has 270 employees on the staff. Among them there are 2 Full Members of RAS, 3 Corresponding Member of RAS, about 30 Doctors of Sciences and more than 80 PhDs. They make studies into actual fields of sciences as follow: control problems, mathematical modeling of complex systems, informatics, mechanics, laser physics, optoelectronics, surface physics and nanotechnologies.

There are several leading scientific schools: quantum electronics (Head - Academician Yu. N. Kulchin), fluid and gas dynamics (Head - Academician of RAS V.A. Levin), surface physics (Head - Corresponding Member of RAS A.A. Saranin). 

The Institute has four regional multiplace access centers equipped by modern analytical facilities to conduct fundamental and applied investigations in the main scientific directions. According these facts, the Institute of Automation and Control Processes forecasts its future with optimism.

Last publications

Abstract The paper studies the possibility of using air temperature and humidity profiles for the determination of pressure in tropical cyclones (TC). The accuracy of air temperature and humidity profile retrieval from AMSU radiometer data is verified using direct radiosonde measurements together with weather station data for the Northwest Pacific. In total, 10 tropical cyclones are analyzed for the period of 2011–2012. The comparison of pressure values inside TC calculated from satellite profiles with weather station data demonstrated good agreement: the linear regression with a slope of 1.014 ± 0.073, a free term of −19 ± 73, and a coefficient of determination R2 = 0.73. TC central pressure values calculated from satellite data were compared with the estimates of the Japan Meteorological Agency exhibiting a satisfactory correspondence with a slope of 1.2. The comparison with the estimates of the Joint Typhoon Warning Center (USA) demonstrates worse agreement.

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Abstract The paper studies the possibility of using air temperature and humidity profiles for the determination of pressure in tropical cyclones (TC). The accuracy of air temperature and humidity profile retrieval from AMSU radiometer data is verified using direct radiosonde measurements together with weather station data for the Northwest Pacific. In total, 10 tropical cyclones are analyzed for the period of 2011–2012. The comparison of pressure values inside TC calculated from satellite profiles with weather station data demonstrated good agreement: the linear regression with a slope of 1.014 ± 0.073, a free term of −19 ± 73, and a coefficient of determination R2 = 0.73. TC central pressure values calculated from satellite data were compared with the estimates of the Japan Meteorological Agency exhibiting a satisfactory correspondence with a slope of 1.2. The comparison with the estimates of the Joint Typhoon Warning Center (USA) demonstrates worse agreement.

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Integration of satellite data and service providers

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Работа посвящена развитию нового метода автоматического совмещения произвольных изображений высокого пространственного разрешения. Совмещение основано на построении плотной сетки реперных точек на двух изображениях. Используется алгоритм SURF для отбора корректных пар реперных точек с расчётом векторов смещений. Смещение каждого пикселя корректируемого изображения рассчитывается посредством осреднения прошедших фильтрацию векторов в заданной окрестности с оценкой точности проведённых расчётов. Работа метода разбирается на двух примерах совмещения изображений прибора Геотон спутника «Ресурс-П» № 1. В первом примере показывается возможность совмещения с пиксельной точностью снимка лесного полога холмистой местности (перепад высот более 200 м), не прошедшего процедуру ортотрансформирования и снятого под углом около 30°. Во втором примере рассмотрено совмещение изображений мультиспектральных и панхроматического каналов прибора Геотон, полученных за один сеанс съёмки. Продемонстрированы пространственные рассогласования изображений. Рассматриваются искажения, возникающие при склейке микрокадров и несовпадении осей приборов, формирующих мультиспектральные изображения. Показано хорошее геометрическое соответствие снимков, если корректно проведён учёт рассогласований углов съёмки.

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Velichko A.S., Gribova V.V., Kolmogorov A.V. Cloud Platform for Decision-Making Support of Digital Production Planning // Computational Technologies. 2019. Vol. 24, No. 6. P. 13–20. (In Russ.) DOI: 10.25743/ICT.2019.24.6.003.

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