Soil Salinization Level Monitoring and Classifying by Mixed Chaotic Systems

Soil salinization process is a complex non-linear dynamic evolution. To classify a system with this type of non-linear characteristic, this study proposed a mixed master/slave chaotic system based on Chua’s circuit and a fractional-order Chen-Lee chaotic system to classify soil salinization level. The subject is the soil in Xinjiang with different levels of human interference. A fractional-order Chen-Lee chaotic system was constructed, and the spectral signal processed by the Chua’s non-linear circuit was substituted into the master/slave chaotic system. The chaotic dynamic errors with different fractional orders were calculated. The comparative analysis showed that 0.1-order has the largest chaotic dynamic error change, which produced two distinct and divergent results. Thus, this study converted the chaotic dynamic errors of fractional 0.1-order into chaotic attractors to build an extension matter-element model. Finally, we compared the soil salt contents (SSC) from the laboratory chemical analysis with the results of the extension theory classification. The comparison showed that the combination of fractional order mixed master/slave chaotic system and extension theory has high classification accuracy for soil salinization level. The results of this system match the result of the chemical analysis. The classification accuracy of the calibration set data was 100%, and the classification accuracy of the validation set data was 90%. This method is the first use of the mixed master/slave chaotic system in this field and can satisfy certain soil salinization monitoring needs as well as promote the application of the chaotic system in soil salinization monitoring.

An educational tool based on finite element method for electromagnetic study

Electromagnetism forms a mandatory topic in the syllabus of undergraduate and graduate courses in electrical engineering. This topic involves many physical and mathematical concepts like curl, divergence, gradient for field determination and representation. These concepts are not only difficult to understand but also often lead to poor learning because of the imaginations and non-visualization of electric and magnetic fields. A correct understanding of fields and its distribution is necessary to understand the working, design and optimization of electrical machines. This paper presents a finite element method (FEM) based educational tool that allows the technical students to visualize electromagnetic (EM) fields inside the EM systems. This tool therefore provides a better understanding of the design and optimization of various electrical devices. This paper shows an example of a 2-pole linear machine to visualize the distribution of the magnetic field in a non-linear circuit. This machine extends to form a linear switched reluctance motor (LSRM) using step-by-step design and optimization procedure along with the user guide interface programmed in FEM based ANSYS Maxwell software. This motor is used as an example to visualize magnetic fields using FEM software in complex circuits and can be used as a good educational tool for students. The paper incorporates the validation of the design procedure through FEM simulations.

Modeling and Electrical Characterization of Josephson Junction Using Approximation in the sense of Least Squares

In order to be able to realize out the mixing detection or harmonic generation functions, a non-linear circuit is necessary for different existing devices and for performing these types of operation, in the submillimetric and / or far-infrared domains (10 μm ≤ λ ≤ 1 mm), the spectral margin covered by this radiation ranging from 300 GHz to 30 THz. In these frequency domains, non-linear point devices are often used, unlike the optical domain where massive devices are widely used, among them the Josephson Junction (JJ) is mainly used in the case where low noise is desired. This paper present electrical characteristic of Josephson Junction (JJ) using Approximation in the sense of Least Squares, for different value of Cj, T, Rj.