Universal system for injection feed of feedstock and air into a vacuum resid oxidation reactor

2008 ◽  
Vol 44 (4) ◽  
pp. 225-230
Author(s):  
S. P. Yakovlev ◽  
A. V. Myl’tsin ◽  
A. N. Yakunin
2020 ◽  
Vol 26 (6) ◽  
pp. 577-583
Author(s):  
L. A. Tuaeva ◽  
I. Z. Toguzova ◽  
S. K. Tokaeva

The presented study develops theoretical and methodological foundations for assessing the fiscal sustainability of the constituent entities of the Russian Federation in perspective.Aim. The study aims to develop a systems approach to assessing the fiscal sustainability of the constituent entities of the Russian Federation in the medium and long term.Tasks. The authors analyze the major approaches to assessing the fiscal sustainability of federal subjects and determine the significance of quantitative and qualitative assessment methods in the development of a methodology for assessing the fiscal sustainability of federal subjects in the medium and long term.Methods. This study uses scientific methods of cognition, analysis and synthesis, comparison and analogy, systems and institutional approaches to assess the fiscal sustainability of federal subjects.Results. The authors examine the major approaches to assessing the fiscal sustainability of federal subjects developed by Russian scientific schools and disciplines; approaches used by state and local authorities; approaches to assessing the fiscal sustainability of federal subjects used by international and national rating agencies; foreign experience. In general, this implies the development of a universal system of indicators for assessing the fiscal sustainability of federal subjects.Conclusions. It is substantiated that under the current conditions of new challenges, particularly in the context of the coronavirus pandemic, it is necessary to assess the long-term balance and sustainability of the budgets of federal subjects using a systems approach based on quantitative and qualitative methods, making allowance for the medium- and long-term prospects to make efficient management decisions at different levels of the economic system.


2017 ◽  
Vol 33 (4) ◽  
pp. 39-46
Author(s):  
T. D. Malyutina

The article substantiates the importance of the company's economic security service in the modern conditions of business operations. The level of security of the enterprise is ensured by high economic potential, financial independence, sustainable development, personnel responsibility. The loss of at least one of the listed elements of a universal system of economic security is characterized by unforeseen consequences for the enterprise. The untimely modernization of the economic security system, its obsolete form, will not ensure the proper level of the company's confident working.


1949 ◽  
Vol 40 (1) ◽  
pp. S8-S12 ◽  
Author(s):  
Robert W. Forrester
Keyword(s):  

2021 ◽  
Vol 297 ◽  
pp. 126648
Author(s):  
Huicheng Ni ◽  
Muhammad Arslan ◽  
Junchao Qian ◽  
Yaping Wang ◽  
Zhigang Liu ◽  
...  

Author(s):  
Anmol L. Purohit ◽  
John A. Misquith ◽  
Brian R. Pinkard ◽  
Stuart J. Moore ◽  
John C. Kramlich ◽  
...  

2020 ◽  
Vol 164 ◽  
pp. 10015
Author(s):  
Irina Gurtueva ◽  
Olga Nagoeva ◽  
Inna Pshenokova

This paper proposes a concept of a new approach to the development of speech recognition systems using multi-agent neurocognitive modeling. The fundamental foundations of these developments are based on the theory of cognitive psychology and neuroscience, and advances in computer science. The purpose of this work is the development of general theoretical principles of sound image recognition by an intelligent robot and, as the sequence, the development of a universal system of automatic speech recognition, resistant to speech variability, not only with respect to the individual characteristics of the speaker, but also with respect to the diversity of accents. Based on the analysis of experimental data obtained from behavioral studies, as well as theoretical model ideas about the mechanisms of speech recognition from the point of view of psycholinguistic knowledge, an algorithm resistant to variety of accents for machine learning with imitation of the formation of a person’s phonemic hearing has been developed.


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