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Li G.-D.,Xinjiang University of Finance and Economics | Zhao G.-M.,Xinjiang University of Finance and Economics | Xu W.-X.,Xinjiang Weather Modification Office | Yao S.-Z.,Beijing University of Civil Engineering and Architecture
Journal of Digital Information Management | Year: 2014

This paper gives a brief introduction of the basic knowledge of Cellular Neural Networks and proposes an image encryption algorithm based on Cellular Neural Networks. The algorithm is based on the unique characteristics of Cellular Neural Networks by using a chaotic system of 5-D CNN as the key source. On this basis, The paper puts forward an image pixel scrambling algorithm based on Logistic chaotic sequence, which realize the image encryption. In this paper, encryption algorithms are programmed and stimulated. The results show that encryption image is the characters of higher pixels' scrambling degree, small correlation between adjacent pixels, strong anti attack, higher security. Source


Jiang H.,Nanjing University of Information Science and Technology | Yin Y.,Nanjing University of Information Science and Technology | Wang X.,Xinjiang Weather Modification Office | Gao R.,Nanjing University of Information Science and Technology | And 3 more authors.
Atmospheric Research | Year: 2016

Investigation of the number concentration of ice nucleating particles (INP) in the deposition nucleation mode during a dust event is reported. The results discussed in this paper are the first continuous INP measurements in Xinjiang, northwest of China, over a period with a strong dust event. The average INP concentration at -. 20 °C and 22% of supersaturation with respect to ice during non-dust days is found around 11 particles per liter, but it reached several hundred per liter in a dust event. A close correlation is also found between the INP number concentration with the number concentration of aerosol particles larger than 0.5 μm in diameter measured during a dust event, which means that a higher concentration of larger particles induced higher INP number concentration. Parameterizations were developed based on measurements to represent the variations of INP concentration with temperature, supersaturation, and the number concentration of aerosol particles with size larger than 0.5 μm. It should be the first ever, as we have known so far, to measure ice nuclei and aerosol properties simultaneously in a desert area and to contrast INP concentrations in dust and dust-free days, and could advancing our understanding of the effects of dust particles on ice nucleation. © 2016 Elsevier B.V. Source


Li G.,Xinjiang University of Finance and Economics | Xu W.,Chengdu University of Information Technology | Wang Y.,Xinjiang Weather Modification Office
Lecture Notes in Electrical Engineering | Year: 2013

In this paper, In terms of the data of stratiform could microphysical structure from airborne particle measurement system (PMS) in 1986-1996 in Xinjiang province. It is a way to detect the time for work in artificial precipitation by the total volume particle. We use traditional way to find the total rain in the cloudy. And then we find the relationship between the time and the total. It will be fit for work when the number is rising and the mean of the rain is more. So we can find the top point in the image, it is the best time to work on artificial rain. © 2013 Springer Science+Business Media. Source


Tong Z.,Xinjiang University of Finance and Economics | Li G.-D.,Xinjiang University of Finance and Economics | Xu W.-X.,Xinjiang Weather Modification Office
Proceedings - 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014 | Year: 2014

This paper argues that the best effect to remove Gaussian noise is to use wiener filtering, and to remove salt & pepper noise to use median filtering will get a better effect. By using the correlation index, and through the original image adding noise and removing noise, it calculates the correlation index of the removal-noise image of the original image is better than traditional methods which used as average filtering and median filtering and wiener filtering to delete the noise of an image. Specifically, this research paper puts forward two results: one is to provide the add noise image first and then to remove the noise, and then to use CNN to detect the image edge, the other is to provide the noise image first by using CNN to detect edge and then to remove the noise. Via these two results compared with the result of the original image edge detection, the conclusion will be as following: in order to avoiding the impact of noise bring to an image, before the image edge detect, one must deal with the noise first. © 2014 IEEE. Source


Li G.,Xinjiang University of Finance and Economics | Xu W.,Xinjiang Weather Modification Office | Xu W.,Chengdu University of Information Technology | Wang X.,Xinjiang Weather Modification Office
Journal of Convergence Information Technology | Year: 2012

Hail identification is one of the most important steps for weather forecast. In this paper, we first present a robustness design theorem for the edgegray detection cellular neural network (EDGE CNN). Then we process some cloud radar images by the EDGE CNN, and the veins of the radar image had been pickup from the figure. The polynomial fitting has been used to analysis the veins figure. Detailed experimental results show that the proposed hail cloudy identification scheme based on CNN can provide more accurate performance to diagnose the cloudy. Source

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