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Zhang X.,Zhengzhou University of Light Industry | Zhang W.,Zhengzhou University of Light Industry | Zhao T.,Zhengzhou University of Light Industry | Wang Y.,Zhengzhou University of Light Industry | And 3 more authors.
Journal of Computational and Theoretical Nanoscience | Year: 2015

The toehold and branch migration domains of traditional DNA strand displacement are covalently connected, which cannot be changed during the execution of the circuit. So to some extent it limits the construction of DNA circuits. Using combinatorial displacement of DNA strands technology wherein toehold and branch migration domains are located in different strands, this problem will be solved. Once these two domains have been linked together by hybridization of the linking domains, it is prepared for DNA strand displacement reaction. Three logic circuits (3-input logic gate, "Inhibit" gate and "XOR") are designed in this paper based on the combinatorial displacement of DNA strands which is theoretically possible. Copyright © 2015 American Scientific Publishers. Source

Zhang X.,Zhengzhou University of Light Industry | Zhang X.,Henan Key Laboratory of Information Based Electrical Appliances | Niu Y.,Zhengzhou University of Light Industry | Cui G.,Zhengzhou University of Light Industry | And 3 more authors.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2010

Invasive weed optimization, which is inspired from the invasive habits of growth of weeds in nature, is a population-based intelligence algorithm. In this paper, we present invasive weed optimization with crossover operation combining the idea of the invasive weed with concepts from evolutionary algorithms. By applying the crossover operation in invasive weed optimization, it not only discourages premature convergence to local optimum but also explores and exploits the promising regions in the search space effectively. This modified algorithm is tested and compared with the standard invasive weed optimization and PSO. The comparative experiments have been conducted on benchmark test functions; invasive weed optimization with crossover operation is able to obtain the result superior to the standard invasive weed optimization and PSO. © 2010 IEEE. Source

Cui G.-Z.,Zhengzhou University of Light Industry | Cui G.-Z.,Henan Key Laboratory of Information Based Electrical Appliances | Li X.-G.,Zhengzhou University of Light Industry | Zhang X.-C.,Zhengzhou University of Light Industry | And 4 more authors.
Jisuanji Xuebao/Chinese Journal of Computers | Year: 2010

The design of DNA sequence is important in improving the reliability of DNA computing. Some appropriate constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. Modified Particle Swarm Optimization/Genetic Algorithm(MPSO/GA) is presented to solve the multi-objective optimization problem. At last the comparison of the results with the known DNA sequences in fitness function value is made to prove the feasibility and efficiency of the method. Source

Li C.,Henan Key Laboratory of Information Based Electrical Appliances | Cao L.,Henan Key Laboratory of Information Based Electrical Appliances | Zhang A.,Henan Key Laboratory of Information Based Electrical Appliances
Proceedings of the 29th Chinese Control Conference, CCC'10 | Year: 2010

The elevator is a kind of complex system with time-varying and strong-coupling characteristics. For elevator systems, with use of traditional PID algorithm, as there are disadvantages of difficult optimal parameters selection, weak steady-state behavior, etc., it is difficult to achieve satisfactory control effect. Therefore, this article discusses the theory of using RBF neural network to identify control object, providing received Jacobian message to BP network, then using arbitrary nonlinear expression ability of BP neural network to achieve the optimum combination of PID control parameters through studying the system, and finally reaching the goal of speedy and stable control. Meanwhile, simulation comparison is made to traditional PID controller on MATLAB and Simulink, and the result shows that the PID controller based on neural networks is faster in response and better in follow nature than the traditional PID controller is. Source

Diao Z.,Zhengzhou University of Light Industry | Diao Z.,Henan Key Laboratory of Information Based Electrical Appliances | Wu B.,Zhengzhou University of Light Industry | Wu B.,Henan Key Laboratory of Information Based Electrical Appliances | And 6 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2015

To overcome the shortages of the existing methods for skeleton lines detection such as low adaptability and meet the needs of recognition for navigation path in modern precision spraying technology system, a new algorithm of skeleton lines detection was proposed based on maximum square principle in this paper. In the first part, pretreatment operation was applied to process the corn crop rows image. Firstly, the improved super green gray transformation algorithm (1.68G-R-B) was used to transfer the corn crop rows color image into gray-scale image and the corn crop rows was separated from the background for the first time. Compared with the traditional gray-scale methods, the improved algorithm in this article not only distinguished the crop rows and background better but also greatly reduced the noise interference and the processing time. Secondly, in order to split the crop rows more clearly, the middle filter operation was used to eliminate background noise. Thirdly, threshold segmentation method was used to convert gray-scale image into a binary image so to prominent the crop rows area further and extinction the background area, and the crop rows and the background were completely separated by the threshold segmentation. In the second part, the corrosion and expansion operation of morphological algorithm were used to process the above binary image. The 3× 3 template element of corrosion was selected to eliminate the background noise that was smaller than the area of crop rows after binarization. The 5×1 template elements of expansion were selected to connect the discontinuous area goodly. In order to get the best contour of the corn crop rows, the times of corrosion and expansion operation was determined by experiment. In the third part, the skeleton of corn crop rows was extracted by maximum square principle that was put forward by this paper. Firstly, the region of crop rows was divided base on symmetry. Secondly, the number of pixels that the value was one in the maximum square of the undetermined skeleton points in each region was written. Finally, comparison of the numbers in each row and the undetermined skeleton points was made so that the one with the most value was selected as target skeleton points. In order to evaluate the advantage of the algorithm, maximum square frame extraction algorithm was compared respectively with morphological skeleton extraction and maximum disk skeleton extraction algorithm which is used extensively by researchers. At the same time, the skeleton line of central crop rows were extracted and linear fitting operation was carried out to verify the accuracy of the algorithm. The random Hough transform was used to get the navigation line because of its advantage. The deviation between the center line of crop rows were fitted and actual navigation line was used to determine the accuracy of skeleton extraction. Image of other crop rows was used to prove the adaptability of the algorithm. Experimental results showed that the new algorithm could not only maintain a single pixel and has strong anti-interference ability of edge noise but also extract the skeleton lines more accurately. In addition, it also could be adapted for the skeleton extraction of other crops as well. And the error of skeleton was less than 5 mm and can satisfy the demand of precision spraying. © 2015, Chinese Society of Agricultural Engineering. All right reserved. Source

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