Applicable Image Security Based on New Hyperchaotic System

Hyperchaotic systems are widely applied in the cryptography domain on account of their more complex dynamical behavior. In view of this, the greatest contribution of this paper is that a two-dimensional Sine coupling Logistic modulated Sine (2D-SCLMS) system is proposed based on Logistic map and Sine map. By a series of analyses, including Lyapunov index (LE), 0–1 test, two complexity analysis methods, and two entropy analysis methods, it is concluded that the new 2D-SCLMS map is hyperchaotic with a wider range of chaos and more complex randomness. The new system combined with two-dimensional Logistic-Sine Coupling Mapping (2D-LSCM) is further applied to an image encryption application. SHA-384 is used to generate the initial values and parameters of the two chaotic systems. Symmetric keys are generated during this operation, which can be applied to the proposed image encryption and decryption algorithms. The encryption process and the decryption process of the new image encryption approaches mainly include pixel scrambling, exclusive NOR (Xnor), and diffusion operations. Multiple experiments illustrate that this scheme has higher security and lower time complexity.

Chaos Theory Methods for Contact-Center Dinamic Control

The work is devoted to searching for optimal control methods for contact center, in particular, methods for predicting the load for further calculation of required number of operators. If the number of operators is always more than required, then the owners of the contact center will incur financial losses. If there are too few employees, the quality of service will decline. Predicting the load of the contact center is required in order to bring the optimal number of operators to work in advance. It is proposed to apply chaos theory to predict the incoming load of a contact center. Positive value of the Lyapunov index indicates the chaotic behavior of the input flow of the load. To predict the load, the methods of linear and nonlinear forecasting and the method of global approximation are used. The paper presents the results of comparing these methods for the problem of predicting the incoming load of contact center.

Improving efficiency of the largest Lyapunov exponent’s estimation by its determination from the vector field properties

Controlling dynamics of nonlinear systems is one of the most important issues in science and engineering. Thus, there is continuous need to study and develop numerical algorithms of control methods. Among the most frequently applied invariants characterizing different aspects of a systems’ dynamics are Lyapunov exponents, fast Lyapunov index, angles of small deviations, fractal dimension or entropy. There exist many different methods of estimation of these indicators. In this paper, modification of our novel method is presented. We have shown that LLE can be estimated from the vector field properties by means of the most basic mathematical operations. Results of efficiency measurements for typical mechanical, electrical and random systems were discussed. We have proved that discussed modification introduced to our method makes the LLE estimation 17–53% faster than using classical algorithms. In addition, unlike the results presented in our previous publication, an improvement in performance was achieved for each of the analyzed cases. As such, the new approach lends to prospective application of LLE not only in dynamical systems' stability investigations, but also in real-time control of systems since the basic calculations and fast, effective method of LLE estimation can be applied even in simple microcontrollers. Our approach could be also applied in investigations of vector field properties, global stability or basins of attraction analyses, allowing for huge time savings.

The Establishment and Dynamic Properties of a New 4D Hyperchaotic System with Its Application and Statistical Tests in Gray Images

In this paper, a new 4D hyperchaotic system is generated. The dynamic properties of attractor phase space, local stability, poincare section, periodic attractor, quasi-periodic attractor, chaotic attractor, bifurcation diagram, and Lyapunov index are analyzed. The hyperchaotic system is normalized and binary serialized, and the binary hyperchaotic stream generated by the system is statistically tested and entropy analyzed. Finally, the hyperchaotic binary stream is applied to the gray image encryption. The histogram, correlation coefficient, entropy test, and security analysis show that the hyperchaotic system has good random characteristics and can be applied to the gray image encryption.

Maximal Predicable Time Scale of Gas Emission about Fully Mechanized Mining Face

Aimed at the issue that predicable time scale is neglected about the current gas emission forecast method, the Lyapunov index method in the chaos theory is adopted to research the predicable time scales of gas emission. The measured data of gas emission about a fully mechanized mining face was investgated. The delay time of time series about gas emission was determined by Non-bias multiple autocorrelation method, and the embedding dimension was determined by G-P algorithm is taken to determine. Based on this, the maximal Lyapunov index of ime series was got and the maximal predicable time scale was got. It is avoided that the time scale is too large when making a prediction of gas emission. On the side, the chaotic time series prediction model can make the correct prediction of gas emission based on the calculation of Lyapunov index value.

Analysis of Vehicle Steering and Driving Bifurcation Characteristics

The typical method of vehicle steering bifurcation analysis is based on the nonlinear autonomous vehicle model deriving from the classic two degrees of freedom (2DOF) linear vehicle model. This method usually neglects the driving effect on steering bifurcation characteristics. However, in the steering and driving combined conditions, the tyre under different driving conditions can provide different lateral force. The steering bifurcation mechanism without the driving effect is not able to fully reveal the vehicle steering and driving bifurcation characteristics. Aiming at the aforementioned problem, this paper analyzed the vehicle steering and driving bifurcation characteristics with the consideration of driving effect. Based on the 5DOF vehicle system dynamics model with the consideration of driving effect, the 7DOF autonomous system model was established. The vehicle steering and driving bifurcation dynamic characteristics were analyzed with different driving mode and driving torque. Taking the front-wheel-drive system as an example, the dynamic evolution process of steering and driving bifurcation was analyzed by phase space, system state variables, power spectral density, and Lyapunov index. The numerical recognition results of chaos were also provided. The research results show that the driving mode and driving torque have the obvious effect on steering and driving bifurcation characteristics.

Lyapunov-Index Application and Time-Frequency Analysis in Medical EEG

With the development of the signal processing and the medical technique, EEG (electroencephalogram) check has been usually used to analyze the brain activity in the clinical medical, which can distinguish the abnormal circadian state from the normal circadian state. Here puts forth Lyapunov index analysis method to analyze the circadian state by the medical personnel or researcher, and the validity of the method is verified in some related graph through computer simulation, and all the method bridges a connection between the Chaos state and the medical EEG diagnoses.