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Search Results: 1 - 10 of 40588 matches for " Shi Peng "
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A Comparative Perception of the Culturally Different Others: Stereotyped or Not
Shi-Yong Peng
Cross-Cultural Communication , 2012, DOI: 10.3968/j.ccc.1923670020120805.2050
Abstract: This paper attempts to explore how American and Chinese college students perceive and are stereotyped towards each other. The data was collected from 150 American college students and 82 Chinese college students. The results are based on the keywords generated from the sentence population produced by the samples. This study finds out that the knowledge of American journalist students of Chinese people and Chinese culture is very shallow, and cultural stereotypes are obvious in their perceptions. The results of the Chinese data show that the knowledge level of Chinese college students about American people and American culture is higher than the knowledge level of American students about Chinese people and Chinese culture. Key words: Cultural stereotypes; Chinese culture; American culture
Dynamically Consistent Nonlinear Evaluations and Expectations
Shi-Ge Peng
Mathematics , 2005,
Abstract: How an economic agent (a firm, an investor or a financial market) evaluates a contingent claim, say a European type of derivatives X, with maturity t? In this paper we study a mechanism of dynamic expectations and evaluations. We give the axiomatic conditions of the time consistency. We prove that, under a domination condition, a time consistent nonlinear evaluation is in fact a g-expectation, i.e., it is completely determined a BSDE in which the generator is a given function g.
Tightness, weak compactness of nonlinear expectations and application to CLT
Shi-Ge Peng
Mathematics , 2010,
Abstract: In this paper we introduce a notion of tightness for a family of nonlinear expectations and show that the tightness can be applied to obtain weak compactness in a framework of nonlinear expectation space. This criterion is very useful for obtaining the weak convergence for a sequence of nonlinear expectations, which is a equivalent to the so-called convergence in distribution, or in law for a sequence of random variables in a nonlinear expectation space. We use the above result to give a new proof to the central limit theorem under a sublinear expectation space. The method can be also applied to prove the convergence of some numerical schemes for degenerate fully nonlinear PDEs.
Stream-Flow Response to Climate Change and Human Activities in an Upstream Catchment of Huai River  [PDF]
Peng Shi, Miao Wu, Xinxin Ma, Simin Qu, Xueyuan Qiao
Journal of Geoscience and Environment Protection (GEP) , 2014, DOI: 10.4236/gep.2014.25010
Abstract:

Climate change and human activities have great implications for hydrological process and water projects planning. In order to evaluate the impacts on stream-flow, statistical methods and SWAT model are applied to this research. The results indicate that the abrupt change year (1965) of annual stream-flow is chosen as the split point of natural and human influenced (particularly reservoirs) periods. The calibrated SWAT model is proved to be applicable in this catchment and is used to simulate the monthly runoff which can be regarded as the natural runoff induced by climate change. A major finding of this study is that the reservoir regulations have apparently altered the monthly and seasonal stream-flow regimes. By quantifying the impacts of climate variation and human activities, the decreasing trend of annual stream-flow is found, and human activities are proved to be the dominant role in the catchment. This research improves our knowledge of hydrological responses to natural and artificial factors, and provides a better understanding for the future reservoir regulations.

Arbuscular Mycorrhizal Fungus Mediate Changes in Mycorrhizosphere Soil Aggregates  [PDF]
Tao Liang, Xiaojun Shi, Tao Guo, Sili Peng
Agricultural Sciences (AS) , 2015, DOI: 10.4236/as.2015.612141
Abstract: Many studies have shown that arbuscular mycorrhizal (AM) fungus has an important role in soil aggregate formation and stabilization. While most studies about the effects of AM fungus on soil aggregate have experimental set-ups in single pots or containers with two compartments, these studies cannot differentiate the effects of roots, mycorrhizal roots or hyphae. In this study we used containers with four compartments to split the roots and quantitatively compare the change of soil aggregate in the mycorrhizosphere soil, rhizosphere soil, hyphosphere soil and bulk soil. Our results demonstrate a significant positive correlation among hyphal length density, easily extractable glomalin (EEG) and aggregate mean weight diameter (MWD), geometric mean diameter (GMD) and percentage of soil macroaggregate with a diameter larger than 0.25 mm (R0.25). The GMD and MWD of R0.25 in the hyphal compartment were higher than those in the non-inoculated root compartment, but were lower than those in the mycorrhizal compartment. This suggests the mycorrhizal hyphae had a greater effect than the non-inoculated roots, but less of an effect than the mycorrhizal roots on the formation and stabilization of soil aggregate. The results reveal that plant roots, mycorrhizal roots and mycorrhizal hyphae contribute to aggregate stability in individual ways and that their effects are additive, creating a synergistic stabilizing effect.
An Immunity-Based IOT Environment Security Situation Awareness Model  [PDF]
Yuanquan Shi, Tao Li, Renfa Li, Xiaoning Peng, Pengju Tang
Journal of Computer and Communications (JCC) , 2017, DOI: 10.4236/jcc.2017.57016
Abstract: To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.
Upregulation of GLE1 and LCP2 Genes in H5N1 Influenza Virus Infected Patients  [PDF]
Wenfeng Peng, Yaping Shi, Baolin Wang, Bo Liu, Zhiyuan Peng, Jianyong Zhang, Ling Chen, Hong Zhang
Advances in Infectious Diseases (AID) , 2016, DOI: 10.4236/aid.2016.63017
Abstract: Previous study showed that the Gle1 RNA export mediator-like (Gle1l) gene and the lymphocyte cytosolic protein 2 (Lcp2) gene were upregulated in response to influenza virus A/Puerto Rico/8/1934 (H1N1) in a mouse mode. To determine whether these two genes were upregulated in humans after influenza A virus infection, nasopharyngeal swabs were collected from eleven patients with flu-like symptoms for viral RNA extraction and PCR amplification. Sequencing analysis revealed that nucleoprotein (NP) gene fragments amplified from nasopharyngeal swabs of four patients shared the highest similarity with the NP gene from avian influenza A (H5N1) virus (A/ goose/Shantou/753/2002). Peripheral blood samples were then collected from four patients for quantitative analysis of GLE1 and LCP2 gene expression. Our results demonstrated that both GLE1 and LCP2 genes were upregulated in H5N1 influenza A virus infected patients, suggesting that upregulation of GLE1 and LCP
Optimal guaranteed cost filtering for Markovian jump discrete-time systems
Magdi S. Mahmoud,Peng Shi
Mathematical Problems in Engineering , 2004, DOI: 10.1155/s1024123x04108016
Abstract: This paper develops a result on the design of robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters. This result extends the steady-state Kalman filter to the case of norm-bounded time-varying uncertainties in the state and measurement equations as well as jumping parameters. We derive a linear state estimator such that the estimation-error covariance is guaranteed to lie within a certain bound for all admissible uncertainties. The solution is given in terms of a family of linear matrix inequalities (LMIs). A numerical example is included to illustrate the theory.
Optimal guaranteed cost filtering for Markovian jump discrete-time systems
Mahmoud Magdi S.,Shi Peng
Mathematical Problems in Engineering , 2004,
Abstract: This paper develops a result on the design of robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters. This result extends the steady-state Kalman filter to the case of norm-bounded time-varying uncertainties in the state and measurement equations as well as jumping parameters. We derive a linear state estimator such that the estimation-error covariance is guaranteed to lie within a certain bound for all admissible uncertainties. The solution is given in terms of a family of linear matrix inequalities (LMIs). A numerical example is included to illustrate the theory.
Demand Modeling, Forecasting, and Counterfactuals, Part I
Parag A. Pathak,Peng Shi
Statistics , 2014,
Abstract: There are relatively few systematic comparisons of the ex ante counterfactual predictions from structural models to what occurs ex post. This paper uses a large-scale policy change in Boston in 2014 to investigate the performance of discrete choice models of demand compared to simpler alternatives. In 2013, Boston Public Schools (BPS) proposed alternative zone configurations in their school choice plan, each of which alters the set of schools participants are allowed to rank. Pathak Shi (2013) estimated discrete choice models of demand using families' historical choices and these demand models were used to forecast the outcomes under alternative plans. BPS, the school committee, and the public used these forecasts to compare alternatives and eventually adopt a new plan for Spring 2014. This paper updates the forecasts using the most recently available historical data on participants' submitted preferences and also makes forecasts based on an alternative statistical model not based a random utility foundation. We describe our analysis plan, the methodology, and the target forecast outcomes. Our ex ante forecasts eliminate any scope for post-analysis bias because they are made before new preferences are submitted. Part II will use newly submitted preference data to evaluate these forecasts and assess the strengths and limitations of discrete choice models of demand in our context.
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