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Field Emission Properties of -C:N Films Deposited on Diamond Substrates
Zong-Yi Qin,Pei-Nan Wang,Hong hen,Xuan-Tong Ying 한국물리학회 2005 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.46 No.2
Amorphous carbon-nitride films were grown on the nitridated diamond substrates by pulsed discharge of nitrogen gas by using graphite rods as the electrodes. The deposition parameters were optimized by monitoring the discharge plasma by optical-emission spectroscopy. It is demonstrated that the films were mainly a mixture of sp2 C-N, sp3 C-N and graphite nanocrystallites. Preliminary results show that deposited films have a cold-cathode-emission property. The threshold field for field emission is about 4.0 V/μm. The linear Fowler-Nordheim characteristic reveals that the fieldemission process is based on the tunneling mechanism.
Study on Interpretable Fuzzy Classification System Based on Neural Networks
Qin Yong,Xing Zong-yi,Jia Li-min,Wu Ying-ying 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper describes a comprehensive method to construct fuzzy classification system considering bothprecision and interpretability. Fuzzy classification system, initialized by modified Gath-Geva fuzzy clustering algorithm, is transformed into neural network. After training the neural network, fuzzy sets similarity measure is adopt to mergeredundant fuzzy sets to improve interpretability, and a constraint genetic algorithm is applied to improve precision. The simulation result on Iris data problem demonstrates the effectiveness of the proposed method
Identification of piRNAs in Hela cells by massive parallel sequencing
( Yi Lu Lu ),( Chao Li ),( Kun Zhang ),( Hua Qin Sun ),( Da Chang Tao ),( Yun Qiang Liu ),( Si Zong Zhang ),( Yong Xin Ma ) 생화학분자생물학회 (구 한국생화학분자생물학회) 2010 BMB Reports Vol.43 No.9
Piwi proteins and Piwi-interacting RNAs (piRNAs) have been implicated in transposon control in germline from Drosophila to mammals. To examine the profile of small RNA expression in human cancer cells and explore difference in small RNA transcriptome, small RNA libraries prepared from wildtype, HILI overexpressed and HILI knockdowned Hela cells were sequenced using Solexa technology. piRNAs and other repeat- associated small RNAs were observed in Hela cells. By using in situ hybridization, piR-49322 was localized in the nucleolus and around the periphery of nuclear membrane in Hela cells. Following the overexpression of HILI, the retrotransposon elements LINE1 was significantly repressed, while LINE1-associated small RNAs decreased in abundance. The present study demonstrated that HILI along with piRNAs plays a role in LINE1 suppression in Hela cancer cell line. [BMB reports 2010; 43(9): 635-641]
Zong-yi Xing,Xue-miao Pang,Hai-yan Ji,Yong Qin,Li-min Jia 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.4
The paper presents an approach to model nonlinear dynamic behaviors of the Automatic Depth Control Electrohydraulic System (ADCES) of a certain minesweeping weapon with Radial Basis Function (RBF) neural networks trained by hierarchical genetic algorithm. In the proposed hierarchical genetic algorithm, the control genes are used to determine the number of hidden units, and the parameter genes are used to identify center parameters of hidden units. In order to speed up conver-gence of the proposed algorithm, width and weight parameters of RBF neural network are calculated by linear algebra methods. The proposed approach is applied to the modelling of the ADCES, and ex-perimental results clearly indicate that the obtained RBF neural network can emulate complex dynamic characteristics of the ADCES satisfactorily. The comparison results also show that the proposed approach performs better than the traditional clustering-based method.
Xing Zong-yi,Zhang Yuan,Qin Yong,Jia Li-min,Wu Ying-ying 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
The paper presents an approach to model the electrohydraulic system of a certain mine-sweeping weapon using the Radial Basis Function (RBF) neural networks. In order to obtain accurate and simple RBF neural networks efficiently, a hierarchical genetic algorithm (HGA) is used to train the neural networks, in which the number of hidden units and the parameters of centers are optimized by the HGA simultaneously. The spread factors and the weights of the neural networks are calculated by the linear algebra methods for relieving computational burden. The proposed algorithm is applied to the modelling of the electrohydraulic system, and the results clearly indicate that the obtained RBF neural network can model the hydraulic system satisfactorily. The comparison results also show that the proposed algorithm performs better than the traditional methods.