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- 저자 : Xiu-wen Lv (검색결과 3 건)
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Hui Liu,Xiu-wen Lv,Shi-chao Chen,Qiang Zhou,Piao Zhou,Wei-lian Qu 한국강구조학회 2023 International Journal of Steel Structures Vol.23 No.1
Welding defects are unavoidable for welded structures, which can lead to fatigue damage even under the random wind load with small amplitude. It is therefore necessary to explore the effect of welding defect on the fatigue properties of welded steel pipes. Three groups of welded steel pipe specimens were designed according to welding defect conditions, i.e. specimens without welding defect (Group I), specimens with incomplete fusion (Group II), and specimens with welding porosity (Group III). Uniaxial tension–compression and torsion high-cycle fatigue tests were carried out. S–N curves of uniaxial tension–compression and torsion tests were obtained by cyclic loading with equal stress amplitude. The test results show that the high-cycle fatigue strength of weldments is obviously lower than that of base metal with the same strength under uniaxial tension–compression and torsion loading. In addition, the welding defects result in a decrease in fatigue strength, while the decrease extent by welding porosity is greater than that by incomplete fusion. Finally, because of the inherent multiaxial loading characteristics of welded structures, the high-cycle multiaxial fatigue life of steel pipe weldments was also predicted by using the modified Wöhler curve method based on the uniaxial fatigue test results. It can be found that when the stress amplitude is constant, the fatigue life of welded steel pipe decreases and the modified Wöhler curves move downward more quickly with the increase of damage parameter defined as the ratio of normal stress amplitude to shear stress amplitude on the critical plane, which means that normal stress amplitude will accelerate the cracks growth and result in faster failure of the weld materials.
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Efficiency Analysis on the Shandong Service Industry based on DEA Method (Data Envelopment Analysis)
Zhang Dong sheng,Zhai Wen xiu,Lv Tian ying 한국유통과학회 2017 KODISA ICBE (International Conference on Business Vol.2017 No.-
In recent years, the development of service industries is oriented on marketing, industrialization and internationalization and maintains productive service industry and life of service industry simultaneously and modern and traditional services simultaneously, promoting the development of service industry and increasing the proportion and the level, which has become the consensus of the people. However, the service industry in Shandong and even around the whole country is still not developed in the whole economic and social development. In this context, using of data envelopment analysis (DEA) to empirically analyze Shandong services from the efficiency of the whole to the industry has great significance in finding out the reasons for the existence inconsistence between the total amount of services and the quality status in Shandong and reasons for over investment on elements of service industry, breaking out the dilemma of the undeveloped status, building the upgrade servicing, realizing the words of president Xi to Shandong "rebirth of phoenix, removing the birds from the cage optimizing the industrial structure; continuing to play a leading role".
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Wang, Jing-Jing,Wu, Hai-Feng,Sun, Tao,Li, Xia,Wang, Wei,Tao, Li-Xin,Huo, Da,Lv, Ping-Xin,He, Wen,Guo, Xiu-Hua Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.10
Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.
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