A Growing Children's Book Publishing Industry in China

Li, Yuanjun

doi:10.4324/9781315134376-6

Cited by 23 publications

(27 citation statements)

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“…Cryptography has been born for a long time, and with the development of the times, cryptography has penetrated into various aspects of people's daily life through its integration with many fields such as mathematics, computer science, biology, and information and communication engineering [11].…”

Section: Cryptographymentioning

confidence: 99%

Research on image encryption algorithm based on one-dimensional logistic and two-dimensional Hénon chaotic system

Wu¹,

Dong²,

Yang³

et al. 2023

International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022)

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Aiming at the problems of high leakage risk and serious information loss that may exist in the encryption and decryption of digital images, an image encryption and decryption algorithm based on chaos theory is proposed. The algorithm introduces both one-dimensional Logistic mapping and two-dimensional Hénon mapping. In the encryption process, the digital image is dislocation encrypted by Logistic mapping and diffusion encrypted by Hénon mapping, and finally the cipher image is obtained. Compared with other similar algorithms, this algorithm has the advantages of low algorithm complexity and high operation efficiency. The simulation experiment is carried out on the MATLAB platform, and the results show that the algorithm can meet the test standard in the field of digital image encryption.

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Section: Cryptographymentioning

confidence: 99%

Research on image encryption algorithm based on one-dimensional logistic and two-dimensional Hénon chaotic system

Wu¹,

Dong²,

Yang³

et al. 2023

International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022)

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“…The average cutting thickness is as follows. 35 where V q is the speed, m/min; n L is the drum speed, r/min; m L is the number of picks on the i -th section line.…”

Section: Nonlinear Dynamic Model Of Gear Systemmentioning

confidence: 99%

Nonlinear dynamics analysis of gear transmission system considering tooth surface friction and thermal deformation

Sheng

Sun

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part K:

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To make the gear better adapt to the high temperature environment, the effects of tooth surface friction and thermal deformation on the dynamic characteristics of the gear were studied. First, based on the basic theory of gear nonlinear dynamics, the backlash model is established considering the effects of thermal deformation. Then, an improved multi-degree-of-freedom nonlinear dynamic model of gears is established taking into account the effects of thermal deformation and friction. The effect of tooth surface friction and thermal deformation on the system motion state is analyzed. Finally, to better analyze the relationship between impact vibration and transmission efficiency, the percussion vibration index is introduced. Compared with the existing research, a gear multi-degree-of-freedom dynamic model is established by considering the influence of tooth surface friction and thermal deformation. The percussion vibration index is introduced as an indicator of gear running health. The research result can provide reference for the optimization and cooling of the gear transmission system.

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“…Li Supeng proposed the internal and external risk control system framework for enterprises. The framework divided the internal and external risk sources faced by enterprises into macro policy risk sources, natural environment risk sources, market risk sources, operational risk sources and financial risk sources and established risk identification and assessment, early warning and response mechanisms [ 7 ]. Kathryn et al divided enterprise risk sources into root risk sources, status risk sources, and unidentified risk sources and analyzed the relationship between risk sources, risk events, and risk management [ 8 ].…”

Section: Related Researchmentioning

confidence: 99%

Research on enterprise knowledge service based on semantic reasoning and data fusion

Yang

Meifang

2021

Neural Comput & Applic

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In the era of big data, the field of enterprise risk is facing considerable challenges brought by massive multisource heterogeneous information sources. In view of the proliferation of multisource and heterogeneous enterprise risk information, insufficient knowledge fusion capabilities, and the low level of intelligence in risk management, this article explores the application process of enterprise knowledge service models for rapid responses to risk incidents from the perspective of semantic reasoning and data fusion and clarifies the elements of the knowledge service model in the field of risk management. Based on risk data, risk decision making as the standard, risk events as the driving force, and knowledge graph analysis methods as the power, the risk domain knowledge service process is decomposed into three stages: prewarning, in-event response, and postevent summary. These stages are combined with the empirical knowledge of risk event handling to construct a three-level knowledge service model of risk domain knowledge acquisition-organization-application. This model introduces the semantic reasoning and data fusion method to express, organize, and integrate the knowledge needs of different stages of risk events; provide enterprise managers with risk management knowledge service solutions; and provide new growth points for the innovation of interdisciplinary knowledge service theory.

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A Growing Children's Book Publishing Industry in China

Cited by 23 publications

References 0 publications

Research on image encryption algorithm based on one-dimensional logistic and two-dimensional Hénon chaotic system

Research on image encryption algorithm based on one-dimensional logistic and two-dimensional Hénon chaotic system

Nonlinear dynamics analysis of gear transmission system considering tooth surface friction and thermal deformation

Research on enterprise knowledge service based on semantic reasoning and data fusion

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