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Institution

Jilin University of Finance and Economics

EducationChangchun, China
About: Jilin University of Finance and Economics is a education organization based out in Changchun, China. It is known for research contribution in the topics: Cluster analysis & Granger causality. The organization has 447 authors who have published 443 publications receiving 2231 citations. The organization is also known as: Changchun Taxation College.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors investigated the resource curse hypothesis in the presence of globalization, human capital, and economic growth in China during the period 1971-2017 and provided more rigorous analysis through several econometric methods, for instance, the Bayer and Hanck cointegration, the Autoregressive Distributed Lag (ARDL), robustness check by fully modified ordinary least squares (FMOLS), DOLS, canonical cointegrating regression (CCR), and Breitung-Candelon spectral Granger causality testing.

140 citations

Journal ArticleDOI
TL;DR: By means of a monotone iterative technique, the existence and uniqueness of the positive solutions for a class of higher conjugate-type fractional differential equation with one nonlocal term are established.

80 citations

Journal ArticleDOI
TL;DR: The archetype method can inform clinicians of VF progression patterns and significantly outperformed AGIS, AGIS scoring, CIGTS scoring, and the permutation of pointwise linear regression (PoPLR).
Abstract: Purpose To detect visual field (VF) progression by analyzing spatial pattern changes. Methods We selected 12,217 eyes from 7360 patients with at least five reliable 24-2 VFs and 5 years of follow-up with an interval of at least 6 months. VFs were decomposed into 16 archetype patterns previously derived by artificial intelligence techniques. Linear regressions were applied to the 16 archetype weights of VF series over time. We defined progression as the decrease rate of the normal archetype or any increase rate of the 15 VF defect archetypes to be outside normal limits. The archetype method was compared with mean deviation (MD) slope, Advanced Glaucoma Intervention Study (AGIS) scoring, Collaborative Initial Glaucoma Treatment Study (CIGTS) scoring, and the permutation of pointwise linear regression (PoPLR), and was validated by a subset of VFs assessed by three glaucoma specialists. Results In the method development cohort of 11,817 eyes, the archetype method agreed more with MD slope (kappa: 0.37) and PoPLR (0.33) than AGIS (0.12) and CIGTS (0.22). The most frequently progressed patterns included decreased normal pattern (63.7%), and increased nasal steps (16.4%), altitudinal loss (15.9%), superior-peripheral defect (12.1%), paracentral/central defects (10.5%), and near total loss (10.4%). In the clinical validation cohort of 397 eyes with 27.5% of confirmed progression, the agreement (kappa) and accuracy (mean of hit rate and correct rejection rate) of the archetype method (0.51 and 0.77) significantly (P < 0.001 for all) outperformed AGIS (0.06 and 0.52), CIGTS (0.24 and 0.59), MD slope (0.21 and 0.59), and PoPLR (0.26 and 0.60). Conclusions The archetype method can inform clinicians of VF progression patterns.

77 citations

Journal ArticleDOI
TL;DR: In this article, a nonlocal initial value problem to a p-Laplacian equation on time scales is studied and the existence of solutions for such a problem is obtained by using the topological degree method.
Abstract: In this paper, a nonlocal initial value problem to a p-Laplacian equation on time scales is studied. The existence of solutions for such a problem is obtained by using the topological degree method.

76 citations

Journal ArticleDOI
TL;DR: In this article, the authors used the theory of planned behaviour to investigate tourists' intention to consume Dayak food when they visit Sarawak, Malaysia, specifically tourists from Peninsular Malaysia, Sabah, Singapore and Indonesia, are sampled to examine and compare consumption intention.

76 citations


Authors

Showing all 460 results

NameH-indexPapersCitations
Limin Wang474099851
Chengqi Wang27434107
Kim-Shyan Fam241112540
Hui Wang19831176
Jianhua Jiang1040310
Ruizhi Li817169
Hui Wang813130
Xuming Han841196
Li Bai724116
Li Zhai78130
Yuan-Yuan Yue713156
Xianqiu Meng6886
Milan Parmar615176
Xiangjun Meng57105
Yujun Chen5587
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20236
20229
202160
202068
201944
201834