This paper examines the identification of patterns of innovative development in the Russian pipeline system. An evaluation system based on the theory of technological innovation cycles is proposed. The innovation cycles identification scheme, in terms of innovation objects, is designed; the innovation dynamics are analyzed on the basis of chronological maps and a comparative evaluation of the waves of innovations in oil transportation is conducted. The influence of industrial specificity of groups of elements on the rate of innovative change is revealed. A forecast of pipeline system elements' innovative renewal is produced using Foresight assessments of priority technologies 2030.
This study determines and presents the capital and operating costs imposed by the use of CO2 capture technologies in the refining and petrochemical sectors. Depending on the refining process and the CO2 capture method, CO2 emissions costs of EUR 30 to 40 per ton of CO2 can be avoided. Advanced low-temperature CO2 capture technologies for upgrading oxyfuel reformers may not provide any significant long-term and short-term benefits compared to conventional technologies. For this reason, an analysis was performed to estimate the CO2 reduction potential for the oil and gas industries using short- and long-term ST/MT technologies, was arriving at a reduction potential of about 0.5–1 Gt/yr. The low cost of CO2 reduction is a result of the good integration of CO2 capture into the oil production process. The results show that advanced gasoline fraction recovery with integrated CO2 capture can reduce the cost of producing petroleum products and reduce CO2 emissions, while partial CO2 capture has comparative advantages in some cases.
a b s t r a c tScene parsing, fully labeling an image with each region corresponding to a label, is one of the core problems of computer vision. Previous methods to this problem usually rely on patchlevel models trained from well labeled data. In this paper, we propose a weakly-supervised scene parsing algorithm that semantically parses a collection of images with multi-label, which is guided by the top-down category models and bottom-up local patch contexts across images that closely related segments usually have similar labels. Images are segmented to patches on multi-level and the contextual relations of patches are discovered via sparse representation by 1 minimization, based on which a graph is constructed. The multi-level spatial context of patches is also embedded in the graph, based on which image-level labels can be propagated to segments optimally. The contextual patch labeling process is formulated in an optimization framework and solved by a convergent iterative method. The category models are learned from the decomposed label representations of the image set and applied to the segments. Final labeling is obtained by combining all the information on pixel level. The effectiveness of the proposed method is demonstrated in experiments on two benchmark datasets and comparisons are taken.
The national strategic goal of the Russian Federation is to ensure the safety of critical technologies and sectors, which are important for the development of the country's oil and gas industry. The article deals with development of national technology for intelligent monitoring of the condition of industrial facilities for transport and storage of oil and gas. The concept of modern monitoring and safety control system is developed focusing on a comprehensive engineering control using integrated automated control systems to ensure the intelligent methodological support for import-substituting technologies. A set of approved algorithms for monitoring and control of the processes and condition of engineering systems is proposed using modular control robotic complexes. Original intelligent models were developed for safety monitoring and classification of technogenic events and conditions. As an example, algorithms for monitoring the intelligent safety criterion for the facilities and processes of pipeline transport of hydrocarbons are presented. The research considers the requirements of federal laws and the needs of the industry.
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