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Search Results: 1 - 10 of 34397 matches for " PENG Si-yao "
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Prompt Optical Emission from Gamma-ray Bursts with Non-single Timescale Variability of Central Engine Activities
Si-Yao Xu,Zhuo Li
Physics , 2013, DOI: 10.1088/1674-4527/14/4/004
Abstract: The complete high-resolution lightcurves of Swift GRB 080319B present an opportunity for detailed temporal analysis of the prompt optical emission. With a two-component distribution of initial Lorentz factors, we simulate the dynamical process of the ejected shells from the central engine in the framework of the internal shock model. The emitted radiation are decomposed into different frequency ranges for a temporal correlation analysis between the lightcurves in different energy bands. The resulting prompt optical and gamma-ray emission show similar temporal profiles, both as a superposition of a slow variability component and a fast variability component, except that the gamma-ray lightcurve is much more variable than its optical counterpart. The variability features in the simulated lightcurves and the strong correlation with a time lag between the optical and gamma-ray emission are in good agreement with the observations of GRB 080319B. Our simulations suggest that the variations seen in the lightcurves stem from the temporal structure of the shells injected from the central engine of gamma-ray bursts. The future high temporal resolution observations of prompt optical emission from GRBs, e.g., by UFFO-Pathfinder and SVOM-GWAC, provide a useful tool to investigate the central engine activity.
Handwritten Chinese character recognition based on double elastic mesh

CHEN Zhang-hui,HUANG Xiao-hui,CHEN Peng-fei,LI Wen-long,ZHU Si-yao,

计算机应用 , 2009,
Abstract: 特征提取是手写体汉字识别的关键,目前四方向网格特征已被实验证实是一种较好的手写体汉字特征.针对通常的纵横弹性网格对汉字"撇、捺"笔画特征提取的不足,提出一种新的网格构造技术--对角弹性网格,它由45°和135°的对角直线构成,将汉字图像划分为多个菱形,能够很好地适应汉字在"撇、捺"方向的变化.将这两种网格单独,以及相互组合成双网格等情况分别进行手写体识别实验,实验结果验证了对角弹性网格的有效性和双弹性网格的高识别率性.
1,5-Diphenylcarbonohydrazide N,N-dimethylformamide
Ai-yun Zhang,Si-yao Ma,Dong Bu
Acta Crystallographica Section E , 2010, DOI: 10.1107/s160053681003922x
Abstract: In the title compound, C13H14N4O·C3H7NO, a 1,5-phenylcarbonohydrazide molecule cocrystallizes with an N,N-dimethylformamide molecule. In the 1,5-phenylcarbonohydrazide molecule, the two phenyl rings are twisted by an angle of 45.8 (5)°. Intermolecular N—H...O hydrogen bonds and weak intermolecular C—H...O interactions contribute to a supramolecular two-dimensional network in the (101) plane.
Electrochemical Preparation and?Photo-Electro Catalytic Properties of Flexible ZnNi/Al-LDHs/Carbon Fibers Composite

TIAN Jing-jing
, CHEN Tao, BAO Xing-chen, GAO Meng-xu, YU Ye-xiao, PENG Si-yao, JIN Guan-ping

- , 2018, DOI: 10.13208/j.electrochem.170726
Abstract: 摘要 本文采用电化学方法,制备了一种便于回收和分离的柔性锌镍/铝层状双羟基/碳纤维(ZnNi/Al-LDHs/CFs) 复合材料. 采用X 射线衍射、红外光谱、场发射扫描电镜、电感耦合等离子体原子发射光谱和电化学阻抗光谱技术表征了ZnNi/Al-LDHs/CFs 复合材料的结构、形貌和光电催化性能. 与单独使用Zn/Al-LDHs/CFs 作为光催化剂或Ni/Al-LDHs/CFs 作为电催化剂相比较,ZnNi/Al-LDHs/CFs 复合材料显示了良好的光-电双功能催化特性,既可被用作乙醇和甲醇氧化的电催化剂,也可光电协同催化 2,6-二氯苯酚降解
A Spiking Neural Network Based Cortex-Like Mechanism and Application to Facial Expression Recognition
Si-Yao Fu,Guo-Sheng Yang,Xin-Kai Kuai
Computational Intelligence and Neuroscience , 2012, DOI: 10.1155/2012/946589
Abstract: In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people’s facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism. 1. Introduction Understanding how rapid exposure to visual stimuli (face, objects) affects categorical decision by cortical neuron networks is essential for understanding the relationship between implicit neural information encoding and explicit behavior analysis. Quantitative psychophysical and physiological experimental evidences support the theory that the visual information processing in cortex can be modeled as a hierarchy of increasingly sophisticated, sparsely coded representations, along the visual pathway [1], and that the encoding using pulses, as a basic means of information transfer, is optimal in terms of information transmission. Such a spiking hierarchy should have the unique ability of decorrelating the incoming visual signals, removing the redundant information, while preserving invariability, in an effort to maximize the information gain [2]. Therefore, characterizing and modeling the functions along the hierarchy, from early or intermediate stages such as lateral geniculate nucleus (LGN), or prime visual cortex (V1), are necessary steps for systematic studies for higher level, more comprehensive tasks such as object recognition. However, the
(ε,δ)-Approximate Aggregation Algorithm in Wireless Sensor Networks

CHENG Si-Yao,LI Jian-Zhong,

软件学报 , 2010,
Abstract: This paper proposes an approximate aggregation algorithm based on Bernoulli sampling to satisfy the requirement of arbitrary precision in wireless sensor networks (WSN). Besides, two sample data adaptive algorithms are also provided. One is to adapt the sample to the varying precision requirement. The other is to adapt the sample to the varying sensed data in networks. Theoretical analysis and experimental results show that the proposed algorithms have good performance in terms of accuracy and energy cost.
Structural Reliability Assessment by Integrating Sensitivity Analysis and Support Vector Machine
Shao-Fei Jiang,Da-Bao Fu,Si-Yao Wu
Mathematical Problems in Engineering , 2014, DOI: 10.1155/2014/586191
Abstract: To reduce the runtime and ensure enough computation accuracy, this paper proposes a structural reliability assessment method by the use of sensitivity analysis (SA) and support vector machine (SVM). The sensitivity analysis is firstly applied to assess the effect of random variables on the values of performance function, while the small-influence variables are rejected as input vectors of SVM. Then, the trained SVM is used to classify the input vectors, which are produced by sampling the residual variables based on their distributions. Finally, the reliability assessment is implemented with the aid of reliability theory. A 10-bar planar truss is used to validate the feasibility and efficiency of the proposed method, and a performance comparison is made with other existing methods. The results show that the proposed method can largely save the runtime with less reduction of the accuracy; furthermore, the accuracy using the proposed method is the highest among the methods employed. 1. Introduction In recent years, a number of structural reliability assessment methods, including first-order reliability method (FORM) [1], response surface method (RSM) [2], and Monte-Carlo simulation method (MCSM) [3], have been developed and applied to practical engineering structures. Among these methods, the FORM is usually used to directly estimate structural failure probability in the case of the explicit limit state functions. In contrast, the RSM and MCSM are widely used in the case that the limit state functions are complex and implicit. The main idea of RSM is to transfer the original implicit limit state function to an approximated explicit expression, which will then be used for the assessment of failure probability with the aid of FORM. However, in most cases, the hypothetical explicit expressions can hardly be found to represent precisely the original nonlinear and complex functions; thus RSM usually causes an unallowable error, even a wrong assessment result. MCSM not only is the most precise method for failure probability assessment, but also solves theoretically all of reliability problems. However, MCSM is a time-consuming process. It is suitable for solving such problem when structural failure probability is small, because a number of samples are required for the purpose of obtaining a reasonable result. To overcome the low-fidelity of RSM and low computing efficiency of MCSM, several researchers have attempted to construct the limit state function based on the intellectual techniques, such as artificial neural networks [4, 5] and SVM [6, 7]. Due to the
Calculation of the Lyapunov exponent for low frequency noise in semiconductor laser and chaos indentification

Yu Si-Yao,Guo Shu-Xu,Gao Feng-Li,

物理学报 , 2009,
Abstract: 根据小波变换和混沌噪声理论,对半导体激光器低频噪声进行了实验和理论分析.应用相轨迹、功率谱、Lyapunov指数、关联维等方法,探讨了噪声混沌模型的可行性.实验证明半导体激光器低频噪声具有混沌特性.在理论上分析了产生混沌的原因,为研究其可靠性提供了理论基础.
Approximate Aggregation of Time-Varying Data in P2P Networks

CHENG Si-Yao,JIANG Shou-Xu,LI Jian-Zhong,

软件学报 , 2009,
Abstract: With the wide application of peer-to-peer (P2P) technologies in many fields such as E-commerce, it is increasingly necessary to do aggregation queries in P2P networks. However, due to the large scale and decentralization of P2P networks it is rather difficult to do this kind of operation. Aggregation queries will become even more difficult in case that the data in P2P networks are time-varying which is often occurs in practice. The existing aggregation methods for data in P2P networks all assume that the data are time-invariant. If these methods are directly applied to P2P networks with time-varying data, some problems will arise because the data used in aggregation processing would have changed owing to the long time of aggregation. So, this paper proposes an approximate aggregation method for time-varying data in P2P networks based on uniform sampling. The theoretical analysis and experimental results show that this aggregation method outperforms the existing methods and can effectively be applied to P2P networks with time-varying data.
A novel method to estimate the parameters of 1/f noise of semiconductor laser diodes

Zhang Zhen-Guo,Gao Feng-Li,Guo Shu-Xu,Li Xue-Yan,Yu Si-Yao,

物理学报 , 2009,
Abstract: 对含白噪声的1/f分形信号小波变换系数的方差随尺度变化的关系进行适当的变换,提出了一种基于最小二乘法的估计半导体激光器1/f噪声参数的新方法.实验表明,该方法可以有效地提取出淹没在白噪声中的激光器1/f噪声,而且估计出的噪声信号的功率谱与对比仪器的测量结果有较好的一致性.
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