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A STATISTICAL INVESTIGATION OF FATIGUE CRACK INITIATION AND GROWTH PROCESS BASED UPON A LARGE SAMPLE SIZE EXPERIMENT
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作者 Min, L Ning, T Yang, QX 《Acta Mechanica Solida Sinica》 SCIE EI 1996年第1期1-12,共12页
After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this p... After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this paper. According to the post-mortem fractographic examination by scanning electron microscopy (SEM), some qualitative observations of the spacial correlation among fatigue striations are developed to reveal the statistical nature of material intrinsic inhomogeneity during the crack growth process. From the test data, an engineering division between crack initiation and growth is defined as the upper limit of small crack. The distributions of crack initiation life N-i, growth life N, and the statistical characteristics of crack growth rate da/dN are also investigated. It is hoped that the work will provide a solid test basis for the study of probabilistic fatigue, probabilistic fracture mechanics, fatigue reliability and its engineering applications. 展开更多
关键词 crack initiation crack growth statistical nature large sample size
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Graph-based Lexicalized Reordering Models for Statistical Machine Translation
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作者 SU Jinsong LIU Yang +1 位作者 LIU Qun DONG Huailin 《China Communications》 SCIE CSCD 2014年第5期71-82,共12页
Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word a... Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method. 展开更多
关键词 natural language processing statistical machine translation lexicalized reordering model reordering graph
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Statistics of China's Natural Gas Production from 2001 to 2006(100 million cubic meters)
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《China Oil & Gas》 CAS 2007年第1期57-57,共1页
关键词 CNPC Statistics of China’s Natural Gas Production from 2001 to 2006 million cubic meters STAR
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Statistics of China's Natural Gas Production from 2000 to 2005(100 million cubic meters)
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《China Oil & Gas》 CAS 2006年第1期37-37,共1页
关键词 STAR Statistics of China’s Natural Gas Production from 2000 to 2005 million cubic meters
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Statistics of China's Natural Gas Production from 2002 to 2007(100 million cubic meters)
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《China Oil & Gas》 CAS 2008年第1期55-55,共1页
关键词 CNPC Statistics of China’s Natural Gas Production from 2002 to 2007 million cubic meters
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Predicting Chinese Abbreviations from Definitions:An Empirical Learning Approach Using Support Vector Regression 被引量:8
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作者 孙栩 王厚峰 王波 《Journal of Computer Science & Technology》 SCIE EI CSCD 2008年第4期602-611,共10页
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however make keyword-based approaches less effective. This paper presents an empirical learning approach to Chinese a... In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however make keyword-based approaches less effective. This paper presents an empirical learning approach to Chinese abbreviation prediction. In this study, each abbreviation is taken as a reduced form of the corresponding definition (expanded form), and the abbreviation prediction is formalized as a scoring and ranking problem among abbreviation candidates, which are automatically generated from the corresponding definition. By employing Support Vector Regression (SVR) for scoring, we can obtain multiple abbreviation candidates together with their SVR values, which are used for candidate ranking. Experimental results show that the SVR method performs better than the popular heuristic rule of abbreviation prediction. In addition, in abbreviation prediction, the SVR method outperforms the hidden Markov model (HMM). 展开更多
关键词 statistical natural language processing abbreviation prediction support vector regression word clustering
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