Method for the synthesis of broadband devices with an optimal characteristic of the power conversion factor, matching the time-varying load impedance.

A method is proposed for the synthesis of broadband matching devices that adapt radio engineering systems to the changing load impedance in a wide range of natural conditions of their operation. The results of experimental studies of the effect of operating conditions on the impedance of VHF and UHF radio antennas with matching devices are presented. An invariant of the sensitivity of the reflection coefficient function to changes in the load impedance is obtained, on the basis of which a complex criterion for the synthesis of broadband matching devices is developed. A broadband matching circuit was synthesized for the AD-44/CW-TA-30-512 antenna device, which provides a gain in the potentially achievable radio line range of up to 5% in relation to the standard matching device. An analytical mathematical model of a broadband matching device is developed and based on it, a matching device adaptive to the changing impedance of the AD-25/CW-3512 antenna is synthesized, providing an average gain in the potentially achievable range of the radio line from 2% to 15% in the framework of the presented experimental studies.

WHO IS AND SHOULD BE A SCIENCE TEACHER

Who is and should be a Science teacher like? This seemingly multiple-time answered ques-tion, however, has not been clearly answered yet; moreover, in this case, a multi-alternative answer is required. Ideas of an optimal characteristic of Science teacher should be defined in context of their main activity. Two alternatives are under the focus; the apparent discrepancy which has been solved in some legal documents, and the state which is frequently not unambiguous in practice.

An Experimental Analysis of Soybean Straw Combustion on Both CO and NOX Emission Characteristics in a Tubular Furnace

In this study, an experiment is conducted to explore the potential to protect both the environment and resource shortage of soybean straw, for combustion in a tubular furnace. Then, the combustion characteristics, gas emissions, and energy consumption of soybean straw are analyzed at a combustion temperature range of 773–1173 K. The results show that the total emissions of CO and NOX are the largest at a temperature of 873 K. For NOX, the emission time is significantly improved at temperatures of 973–1173 K. At high temperatures, the reaction of NOX with CO and coke reduces the total emission of NOX. The average weight loss rate at combustion temperatures of 973, 1073, and 1173 K increased by 27.38%, 61.47% and 77.97%, respectively, relative to that of 873 K. However, the energy consumption increases with the increase in combustion temperature, resulting in unnecessary waste. To get an optimal characteristic between energy utilization and pollutant discharge, a temperature range of 873–973 K is determined as the appropriate temperature for burning soybean straw.

Curvelet Transform Based EEG Signal Analysis using Pca

The knowledge of Brain-Computer Interface (BCI) provides a direct exchange of information from the human brain and external devices. In BCI design structure, electroencephalography (EEG) identifies to be the major deliberately calculate the recordings of brain activity. Our proposed method is used to extract and analyze the characteristics of the EEG signal. They organize signal for BCI can be discriminate against and serve up human emotions. The projected method recognizes EEG information retrieving and computing feature extraction and classification. These signals have dissimilar frequency stages for Data waves, theta, alpha and beta. The combination of curvelet transforms (CT) and the principal component analysis (PCA) compute the dimensionality minimize and optimal characteristic extraction. The categorization of EEG signals, ANN (Artificial Neural Network) impact on this process of classification. This paper also provides a similarity between the projected two tools PCA and CT, with a combination of ANN.

Detection of Wampee Damage based on Hyperspectral Imaging Technology

Wampee is one of the characteristic fruits in southern China, and its brittle and thin skin can easily be damaged. In this study, principal components analysis (PCA) and minimum noise fraction (MNF) analysis were carried out on the two wampee varieties by hyperspectral imaging technology, and 680nm was determined to be the optimal characteristic wavelength. The accurate recognition rate obtained from PCA algorithm for wampee samples of two varieties was about 83.75%, and that obtained from MNF algorithm for two variety samples was 85%. It was indicated that the wampee damaged can be identified more accurately and effectively by MNF based on hyperspectral imaging technology

Characteristic wavelength selection of volatile organic compounds infrared spectra based on improved interval partial least squares

As important components of air pollutant, volatile organic compounds (VOCs) can cause great harm to environment and human body. The concentration change of VOCs should be focused on in real-time environment monitoring system. In order to solve the problem of wavelength redundancy in full spectrum partial least squares (PLS) modeling for VOCs concentration analysis, a new method based on improved interval PLS (iPLS) integrated with Monte-Carlo sampling, called iPLS-MC method, was proposed to select optimal characteristic wavelengths of VOCs spectra. This method uses iPLS modeling to preselect the characteristic wavebands of the spectra and generates random wavelength combinations from the selected wavebands by Monte-Carlo sampling. The wavelength combination with the best prediction result in regression model is selected as the characteristic wavelengths of the spectrum. Different wavelength selection methods were built, respectively, on Fourier transform infrared (FTIR) spectra of ethylene and ethanol gas at different concentrations obtained in the laboratory. When the interval number of iPLS model is set to 30 and the Monte-Carlo sampling runs 1000 times, the characteristic wavelengths selected by iPLS-MC method can reduce from 8916 to 10, which occupies only 0.22% of the full spectrum wavelengths. While the RMSECV and correlation coefficient (Rc) for ethylene are 0.2977 and 0.9999[Formula: see text]ppm, and those for ethanol gas are 0.2977 ppm and 0.9999. The experimental results show that the iPLS-MC method can select the optimal characteristic wavelengths of VOCs FTIR spectra stably and effectively, and the prediction performance of the regression model can be significantly improved and simplified by using characteristic wavelengths.

Analysis of Ecological of Characteristic Time for Thermoacoustic Refrigerator by Double Acoustic Drivers

Using the method of finite time thermodynamics, and quoting the ecology objective function to optimize the performance of the dual sound source driven thermoacoustic refrigerator regenerator. And Use the characteristic time to characterize the transducer effect in the thermoacoustic system in order to seek the optimal relationship between the characteristic time and ecology objective function. Numerical calculation results show that the impact of the relationship between ecological function and the characteristic time is parabolic curve, so there is an optimal characteristic time to maximize ecological objective function values.