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RISS 인기검색어
- 검색키워드
- 저자 : Zhangjun Liu (검색결과 4 건)
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Dimension-reduction simulation of stochastic wind velocity fields by two continuous approaches
Zhangjun Liu,Chenggao He,Zenghui Liu,Hailin Lu 한국풍공학회 2019 Wind and Structures, An International Journal (WAS Vol.29 No.6
In this study, two original spectral representations of stationary stochastic fields, say the continuous proper orthogonal decomposition (CPOD) and the frequency-wavenumber spectral representation (FWSR), are derived from the Fourier-Stieltjes integral at first. Meanwhile, the relations between the above two representations are discussed detailedly. However, the most widely used conventional Monte Carlo schemes associated with the two representations still leave two difficulties unsolved, say the high dimension of random variables and the incompleteness of probability with respect to the generated sample functions of the stochastic fields. In view of this, a dimension-reduction model involving merely one elementary random variable with the representative points set owing assigned probabilities is proposed, realizing the refined description of probability characteristics for the stochastic fields by generating just several hundred representative samples with assigned probabilities. In addition, for the purpose of overcoming the defects of simulation efficiency and accuracy in the FWSR, an improved scheme of non-uniform wavenumber intervals is suggested. Finally, the Fast Fourier Transform (FFT) algorithm is adopted to further enhance the simulation efficiency of the horizontal stochastic wind velocity fields. Numerical examples fully reveal the validity and superiority of the proposed methods.
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Numerical investigation of a novel device for bubble generation to reduce ship drag
Zhang, Jun,Yang, Shuo,Liu, Jing The Society of Naval Architects of Korea 2018 International Journal of Naval Architecture and Oc Vol.10 No.5
For a sailing ship, the frictional resistance exerted on the hull of ship is due to viscous effect of the fluid flow, which is proportional to the wetted area of the hull and moving speed of ship. This resistance can be reduced through air bubble lubrication to the hull. The traditional way of introducing air to the wetted hull consumes extra energy to retain stability of air layer or bubbles. It leads to lower reduction rate of the net frictional resistance. In the present paper, a novel air bubble lubrication technique proposed by Kumagai et al. (2014), the Winged Air Induction Pipe (WAIP) device with opening hole on the upper surface of the hydrofoil is numerically investigated. This device is able to naturally introduce air to be sandwiched between the wetted hull and water. Propulsion system efficiency can be therefore increased by employing the WAIP device to reduce frictional drag. In order to maximize the device performance and explore the underlying physics, parametric study is carried out numerically. Effects of submerged depth of the hydrofoil and properties of the opening holes on the upper surface of the hydrofoil are investigated. The results show that more holes are favourable to reduce frictional drag. 62.85% can be achieved by applying 4 number of holes.
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Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images
Zhang, Jun,Liu, Mingxia,Le An,Gao, Yaozong,Shen, Dinggang IEEE 2017 IEEE Journal of Biomedical and Health Informatics Vol.21 No.6
<P>Structural magnetic resonance imaging (MRI) has been proven to be an effective tool for Alzheimer's disease (AD) diagnosis. While conventional MRI-based AD diagnosis typically uses images acquired at a single time point, a longitudinal study is more sensitive in detecting early pathological changes of AD, making it more favorable for accurate diagnosis. In general, there are two challenges faced in MRI-based diagnosis. First, extracting features from structural MR images requires time-consuming nonlinear registration and tissue segmentation, whereas the longitudinal study with involvement of more scans further exacerbates the computational costs. Moreover, the inconsistent longitudinal scans (i.e., different scanning time points and also the total number of scans) hinder extraction of unified feature representations in longitudinal studies. In this paper, we propose a landmark-based feature extraction method for AD diagnosis using longitudinal structural MR images, which does not require nonlinear registration or tissue segmentation in the application stage and is also robust to inconsistencies among longitudinal scans. Specifically, first, the discriminative landmarks are automatically discovered from the whole brain using training images, and then efficiently localized using a fast landmark detection method for testing images, without the involvement of any nonlinear registration and tissue segmentation; and second, high-level statistical spatial features and contextual longitudinal features are further extracted based on those detected landmarks, which can characterize spatial structural abnormalities and longitudinal landmark variations. Using these spatial and longitudinal features, a linear support vector machine is finally adopted to distinguish AD subjects or mild cognitive impairment (MCI) subjects from healthy controls (HCs). Experimental results on the Alzheimer's Disease Neuroimaging Initiative database demonstrate the superior performance and efficiency of the proposed method, with classification accuracies of 88.30% for AD versus HC and 79.02% for MCI versus HC, respectively.</P>
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Zhang, Jun,Wang, Rui,Ma, Yan-Yun,Chen, Lin-Qi,Jin, Bo-Han,Yu, Hua,Wang, Jiu-Cun,Gao, Chun-Fang,Liu, Jie Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11
Hepatocellular carcinoma (HCC) is one of the most prevalent cancers in the world and deeply threatens people's health, especially in China. Techniques of early diagnosis, prevention and prediction are still being discovered, among which the approaches based on single nucleotide polymorphisms in microRNA genes (miRNA SNPs) are newly proposed and show prospective potential. In particular, the association between SNPs in miRNA196a-2 (rs11614913) and miRNA146a (rs2910164) and HCC has been investigated. However, the conclusions made were conflicting, possibly due to insufficient sample size or population stratification. Further confirmations in well-designed large samples are still required. In this study, we verified the association between these two SNPs and the susceptibility to HCC by MassARRAY assay in a 2,000 large Chinese case-control sample. Significant association between rs11614913 and HCC was confirmed. Subjects with the genotype of CT+TT or T allele in rs11614913 were more resistant to HCC (CT+TT: OR (95% CI)=0.73 (0.57-0.92), P=0.01; T allele: OR (95% CI)=0.85 (0.75-0.97), P=0.02) and HBV-related HCC (CT+TT: OR (95% CI)=0.69 (0.53-0.90), P=0.01; T allele: OR (95% CI)=0.82 (0.71-0.95), P=0.01). The affected carriers of CT or TT also tended to have lower levels of serum AFP (P=0.01). This study demonstrated a role of rs11614913 in the etiology of HCC. Further research should focus on the clinical use of this miRNA SNP, so as to facilitate conquering HCC.
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