Computer worms in control automation systems: Risk dynamics

2021 ◽  
Author(s):  
A. V. Popov ◽  
A. L. Serdechniy ◽  
Y. G. Pasternak ◽  
A. A. Zaslavskiy ◽  
V. S. Zarubin
Keyword(s):  
Computer Worms ◽  
Automation Systems ◽  
Risk Dynamics ◽  
Control Automation

Implementation of Trojan programs in management automation systems: Risk dynamics

2021 ◽  
Author(s):  
P. A. Antsupov ◽  
A. L. Serdechniy ◽  
E. A. Moskaleva ◽  
V. M. Pitolin ◽  
N. I. Barannikov
Keyword(s):  
Automation Systems ◽  
Risk Dynamics

Automatic Control System for Gas Turbines Test Rig

2013 ◽  
Vol 436 ◽  
pp. 398-405
Author(s):  
Gabriel Dediu ◽  
Daniel Eugeniu Crunteanu
Keyword(s):  
Working Conditions ◽  
Gas Turbines ◽  
Command And Control ◽  
Test Rig ◽  
Maintenance Costs ◽  
Automation Systems ◽  
Control Automation ◽  
Complete Automation ◽  
And Control ◽  
Efficiency And Reliability

The technical evolution of the industrial and aeronautical groups involving gas turbines, determined by the request of increased efficiency and reliability, imposes the control through modern command and control automation systems. The paper describes a system destined to safely monitor, command and control the working conditions through complete automation of all command functions of a gas turbine. The system is suitable for all series of applications involving gas turbines, also providing a decrease in exploitation and maintenance costs.

Human-Agent Interactions: Does Accountability Matter in Interactive Control Automation?

2018 ◽  
Vol 62 (1) ◽  
pp. 1643-1647 ◽  
Author(s):  
Pouria Salehi ◽  
Erin K. Chiou ◽  
Adam Wilkins
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Supervisory Control ◽  
Cognitive Task ◽  
Interactive Control ◽  
Agent Interactions ◽  
Human Agent ◽  
Joint Task ◽  
Automation Systems ◽  
Control Automation

In human-automation systems, where high situation awareness is associated with better decision-making, understanding accountability may be crucial to preventing automation complacency. In supervisory control automation, there is some evidence that accountability increases human-automation performance; however, with increasingly intelligent automated agents, human-agent work relationships may resemble more interactive control compared to supervisory control. We investigate the effects of social accountability in a simulated joint task environment and hypothesize that people under an accountability condition would cooperate more with an automated agent than people under a non-accountability condition, in a shared cognitive task. Results from our study support this hypothesis. However, for the accountability group, people’s performance in terms of units processed was lower, and this group also self-reported lower performance and attentional control, with higher frustration. These findings indicate that accountability may slow the decision-making process through added pressure, with some costs to short term efficiency.

scholarly journals Implementation of modern approaches to development and testing of advanced driver assistance systems, including driverless systems

2021 ◽  
Vol 2061 (1) ◽  
pp. 012121
Author(s):  
D V Endachev ◽  
S V Bakhmutov ◽  
V V Evgrafov ◽  
N P Mezentsev ◽  
V A Ryazantsev ◽  
...  
Keyword(s):  
Computer Vision ◽  
Visual Recognition ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Vision Systems ◽  
Advanced Driver Assistance Systems ◽  
Automation Systems ◽  
Control Automation ◽  
Computer Vision Systems ◽  
Assistance Systems

Abstract The paper describes FSUE “NAMI” competences in the field of on-board Advanced Driver Assistance Systems (ADAS) and driverless systems for automated vehicle driving. In recent years, FSUE “NAMI” has developed a number of prototype advanced driver assistance systems and vehicle driving automation systems. In order to comprehensively address the control automation tasks, the first SHATL prototype was developed, which was a demonstrator of capabilities of the fully digital control over the vehicle. SUE “NAMI” specialists conduct developments in three primary focus areas of computer vision systems evolution: visual recognition, radar technologies and lidar technologies. In modern technical systems, they are used cumulatively in order to increase the reliability and level of sophistication of computer vision systems, including the redundancy (reservation) principle.

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