Automated Control Parameters Systems of Technological Process Based on Multiprocessor Computing Systems

Shvachych, Gennady; Moroz, Boris; Pobocii, Ivan; Kozenkov, Dmytro; Busygin, Volodymyr

doi:10.1007/978-3-030-17798-0_53

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…In this regard, this direction is promising in terms of the implementation of the proposed research. The paper research demonstrates that one of the main problems of the studied technologies is in the features of the modeling process, both machine and mathematical [19][20][21][22]. For instance, for servicing and solving security problems of those technologies, it is necessary to use powerful computing equipment and high-performance ones.…”

Section: Discussionmentioning

confidence: 99%

Development of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology

Shvachych

Pobochii

Sashchuk

et al. 2022

Smart Innovation, Systems and Technologies

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The paper proposes and explores a new blockchain system that operates on a linearly scalable consensus mechanism. This selection method confirms the shard through shares voting and scalable random generation by VDF (Verifiable Delay Function) and VRF (Verifiable Random Function). The system analyzes available consensus mechanisms, sharding, and the age of distributed randomness. It is energy efficient, fully scalable, secure, with fast consensus. Compared to available methods, the improved shard method performs network connection and transaction verification and reveals the state of the blockchain. The threshold has a sufficiently low coefficient for small validators to participate in the network and receive rewards. The proposed sharding process runs securely due to a distributed randomness (DRG) process that is unpredictable, impartial, and verified. The network is constantly overloaded to prevent slow adaptive Byzantine malicious validators. Contrary to other sharding blockchains that require Proof-of-Work to select validators, the proposed consensus is attributed to Proof-of-Stake, therefore, energy-efficient. Herein the consensus is achieved by a BFT algorithm which is linearly scalable and faster than PBFT.

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Section: Discussionmentioning

confidence: 99%

Development of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology

Shvachych

Pobochii

Sashchuk

et al. 2022

Smart Innovation, Systems and Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…At present, a large number of complex thermal power plants (nuclear and chemical reactors, turbines, powerful boilers, various furnaces for smelting metal, etc.) are equipped with automated control systems for technological parameters [5][6][7]. The controlled parameters, in addition to information about the flow of technological processes, also contains information about the current state of the equipment, the appearance and development of various faults [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Predicting anomaly conditions of energy equipment using neural networks

Sverdlova

Zaporozhets

2021

E3S Web Conf.

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In modern conditions for complex thermal power facilities, the issue of developing methods for predicting equipment failures is especially relevant. Methods based on the intellectualization of diagnostic systems and allowing to obtain predictive models based on the use of both current data received in real time from measuring equipment and retrospective information are considered promising. Intellectualization of the system in terms of the ability to learn allows to quickly adjust the parameters of forecasting models under changing conditions of equipment operation, to determine new deadlines for scheduled repairs and minimize equipment downtime. A limitation of the use of methods is the incompleteness of failure statistics, ie when equipment failures are rare or non-existent. Such diagnostics of energy equipment, especially thermal power facilities, contributes to a more environmentally friendly production.

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Designing Features of Parallel Computational Algorithms for Solving of Applied Problems on Parallel Computing Systems of Cluster Type

Shvachych

Busygin

Tetyana

et al. 2019

Inventive Computation Technologies

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Automated Control Parameters Systems of Technological Process Based on Multiprocessor Computing Systems

Cited by 4 publications

References 2 publications

Development of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology

Development of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology

Predicting anomaly conditions of energy equipment using neural networks

Designing Features of Parallel Computational Algorithms for Solving of Applied Problems on Parallel Computing Systems of Cluster Type

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