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Search Results: 1 - 10 of 25851 matches for " Ning Han "
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Collective Management System of Internet Copyright under the Principle of Balance of Interests
Ning Han
Asian Social Science , 2012, DOI: 10.5539/ass.v8n8p177
Abstract: With acceleration of the progress of networking, realization and protection means of copyright can no longer suit with the developmental need of information technology. The principle of balance of interests is the core of intellectual property system and improvement of collective management system of copyright in the internet environment can economically and effectively guarantee realization of balance of interests.
Study on the Construction of Perfecting the Collective Administration System of Network Copyright
Ning Han
Journal of Politics and Law , 2011, DOI: 10.5539/jpl.v4n2p139
Abstract: The collective administration of copyright is the system designed to protect and administrate the copyright. In nature, the collective administration of copyright is a kind of civil rights administration system, and a kind of concrete form of trust. With the development of the networking society, it is urgent to strengthen and perfect the collective administration system in network environment.
A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models
Yang Ning,Han Liu
Statistics , 2014,
Abstract: We consider the problem of uncertainty assessment for low dimensional components in high dimensional models. Specifically, we propose a decorrelated score function to handle the impact of high dimensional nuisance parameters. We consider both hypothesis tests and confidence regions for generic penalized M-estimators. Unlike most existing inferential methods which are tailored for individual models, our approach provides a general framework for high dimensional inference and is applicable to a wide range of applications. From the testing perspective, we develop general theorems to characterize the limiting distributions of the decorrelated score test statistic under both null hypothesis and local alternatives. These results provide asymptotic guarantees on the type I errors and local powers of the proposed test. Furthermore, we show that the decorrelated score function can be used to construct point and confidence region estimators that are semiparametrically efficient. We also generalize this framework to broaden its applications. First, we extend it to handle high dimensional null hypothesis, where the number of parameters of interest can increase exponentially fast with the sample size. Second, we establish the theory for model misspecification. Third, we go beyond the likelihood framework, by introducing the generalized score test based on general loss functions. Thorough numerical studies are conducted to back up the developed theoretical results.
Soil water resources use limit in the loess plateau of China  [PDF]
Ting Ning, Zhongsheng Guo, Mancai Guo, Bing Han
Agricultural Sciences (AS) , 2013, DOI: 10.4236/as.2013.45B019

Soil water is a key factor limiting plant growth in water-limited regions. Without limit of soil water used by plants, soil degradation in the form of soil desiccation is easy to take place in the perennial forestland and grassland with too higher density or productivity. Soil water resources use limit (SWRUL) is the lowest control limit of soil water resources which is used by plants in those regions. It can be defined as soil water storage within the maximum infiltration depth in which all of soil layers belong to dried soil layers. In this paper, after detailed discussion of characteristics of water resources and the relationship between soil water and plant growth in the Loess Plateau, the definition, quantitative method, and practical applications of SWRUL are introduced. Henceforth, we should strengthen the study of SWRUL and have a better understanding of soil water resources. All those are of great importance for designing effective restoration project and sustainable management of soil water resources in water- limited regions in the future.

Developing the Upgrade Detection and Defense System of SSH Dictionary-Attack for Multi-Platform Environment  [PDF]
Yen-Ning Su, Guang-Han Chung, Benjamin Jenghorng Wu
iBusiness (IB) , 2011, DOI: 10.4236/ib.2011.31011
Abstract: Based on the improved algorithm for analyzing log and the detection and defense system of SSH Dictionary-Attack for Multi-Platform Environment (Su, Chen, Chung & Wu), we developed the upgrade detection and defense system of SSH Dictionary-Attack for Multi-Platform Environment. In this study, we introduced the current threats and the types of SSH Dictionary-Attack. Then, we explained the functions and differences between the current defense software and defense types of SSH Dictionary-Attack; and described the current system of SSH Dictionary-Attack for Multi-Platform Environment. Moreover, based on the study of Su, Chen, Chung and Wu, we improved the algorithm of analyzing log in order to increase the defense capability of SSH Dictionary-Attack. After that, we designed the upgrade detection and defense system of SSH Dictionary-Attack for Multi-Platform Environment. The contribution of this study is to provide the upgrade detection and defense system of SSH Dictionary-Attack which was to keep the functions of original system of SSH Dictionary-Attack, and to improve the effectiveness of the algorithm of analyzing log.
Synthesis and Surface Activity of Cashew-Based Anion-Nonionic Surfactants  [PDF]
Haiyan Li, Jun Wang, Jun Han, Cuiqin Li, Mengmeng Ning, Changhuan Liu
Open Journal of Applied Sciences (OJAppS) , 2012, DOI: 10.4236/ojapps.2012.22012
Abstract: Four novel anion-nonionic surfactants were synthesized using cashew phenol as raw material. The four structures were characterized by IR and elemental analysis. Their surface activities were investigated. Their critical micelle concentrations (CMC) are 9.30 × 10 –3 mol/L, 8.50 × 10–3 mol/L, 8.10 × 10–3 mol/L and 7.71 ×–3 mol/L respectively, and the corresponding surface tensions at CMC are 28.38 mN/m, 28.60 mN/m, 30.40 mN/m and 30.00 mN/m respectively. The contact angles of the solutions on sheet galsses were measured to observe their surface wettabilities. The effects of their concentrations, the concentrations of NaCl and temperature on their foaming capacity and foam stability were studied.
Pathologico-Anatomic Categories of Choledochal End-Piece Stenosis Due to Chronic Pancreatitis and Clinical Significance  [PDF]
Yunfu Lv, Xiaoguan Gong, Xiaoyu Han, Shunwu Chang, Ning Liu, Baochun Wang
Open Journal of Endocrine and Metabolic Diseases (OJEMD) , 2013, DOI: 10.4236/ojemd.2013.34030

Background: Chronic pancreatitis caused by common bile duct segment stenosis is a common complication. It often results in near side bile duct expansion, bile drain disorder, appearing serious obstructive jaundice, biliary cirrhosis, lifethreatening. However, chronic pancreatitis causes not bravery manager narrow some light, some heavy, and the clinical manifestation is different too. We think there may be different kinds of pathological anatomy. As a result, we carried out the research of this subject. Objective: To investigate the anatomicopathological classification of terminal stenosis of the common bile duct (CBD) caused by chronic pancreatitis (CP) and the treatment. Method: A retrospective analysis was made for the management of sympatomatic stenosis of the terminal end of CBD 47 CP cases. Autopsy was performed in 25 bodies to verify our classification. Result: By analyzing operation and postoperative follow-ups to 47 patients with obvious choledochal dilatations (diameter 15 mm) due to chronic pancreatitis, the authors have found that there exist three pathologico-anatomic categories of choledochal end-piece stenosis due to chronic pancreatitis. The stenosis of type

On Semiparametric Exponential Family Graphical Models
Zhuoran Yang,Yang Ning,Han Liu
Statistics , 2014,
Abstract: We propose a new class of semiparametric exponential family graphical models for the analysis of high dimensional mixed data. Different from the existing mixed graphical models, we allow the nodewise conditional distributions to be semiparametric generalized linear models with unspecified base measure functions. Thus, one advantage of our method is that it is unnecessary to specify the type of each node and the method is more convenient to apply in practice. Under the proposed model, we consider both problems of parameter estimation and hypothesis testing in high dimensions. In particular, we propose a symmetric pairwise score test for the presence of a single edge in the graph. Compared to the existing methods for hypothesis tests, our approach takes into account of the symmetry of the parameters, such that the inferential results are invariant with respect to the different parametrizations of the same edge. Thorough numerical simulations and a real data example are provided to back up our results.
Testing and Confidence Intervals for High Dimensional Proportional Hazards Model
Ethan X. Fang,Yang Ning,Han Liu
Statistics , 2014,
Abstract: This paper proposes a decorrelation-based approach to test hypotheses and construct confidence intervals for the low dimensional component of high dimensional proportional hazards models. Motivated by the geometric projection principle, we propose new decorrelated score, Wald and partial likelihood ratio statistics. Without assuming model selection consistency, we prove the asymptotic normality of these test statistics, establish their semiparametric optimality. We also develop new procedures for constructing pointwise confidence intervals for the baseline hazard function and baseline survival function. Thorough numerical results are provided to back up our theory.
A Likelihood Ratio Framework for High Dimensional Semiparametric Regression
Yang Ning,Tianqi Zhao,Han Liu
Statistics , 2014,
Abstract: We propose a likelihood ratio based inferential framework for high dimensional semiparametric generalized linear models. This framework addresses a variety of challenging problems in high dimensional data analysis, including incomplete data, selection bias, and heterogeneous multitask learning. Our work has three main contributions. (i) We develop a regularized statistical chromatography approach to infer the parameter of interest under the proposed semiparametric generalized linear model without the need of estimating the unknown base measure function. (ii) We propose a new framework to construct post-regularization confidence regions and tests for the low dimensional components of high dimensional parameters. Unlike existing post-regularization inferential methods, our approach is based on a novel directional likelihood. In particular, the framework naturally handles generic regularized estimators with nonconvex penalty functions and it can be used to infer least false parameters under misspecified models. (iii) We develop new concentration inequalities and normal approximation results for U-statistics with unbounded kernels, which are of independent interest. We demonstrate the consequences of the general theory by using an example of missing data problem. Extensive simulation studies and real data analysis are provided to illustrate our proposed approach.
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