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您的检索式：作者名="Junchen Jin"
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| 1 | Transparently curved metamaterial with broadband millimeter wave absorption显示文摘We present a conformal metamaterial with simultaneous optical transparency and broadband millimeter-wave absorption for a curved surface. By tailoring the reflection response of meta-atoms at oblique angles, it is possible to achieve excellent absorption performance from 26.5 to 40.0 GHz within a wide angular range from 0° to 60°for transverse-electric and transverse-magnetic waves. In the meantime, by employing transparent substrates,including polyvinyl chloride and polyethylene terephthalate, good optical transmittance(80.1%) and flexibility are obtained simultaneously. The reflectivity of a curved metallic surface coated with the proposed curved metamaterial is simulated and measured experimentally. Both results demonstrate excellent absorption performance of the metamaterial, which is highly favored for practical applications. | CHENG ZHANG JIN YANG WENKANG CAO WEI YUAN JUNCHEN KE LIUXI YANG QIANG CHENG TIEJUN CUI | 2019 | Photonics Research2019，7，4： | 7 |
| 2 | Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study:principal components analysis vs.partial least squares显示文摘With recent advances in biotechnology, genome-wide association study(GWAS) has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression(LR) based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression(PC-LR), partial least squares-based logistic regression(PLS-LR), have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor?mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism(SNP) set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis.On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data. | Honggang Yi Hongmei Wo Yang Zhao Ruyang Zhang Junchen Dai Guangfu Jin Hongxia Ma Tangchun Wu Zhibin Hu Dongxin Lin Hongbing Shen Feng Chen | 2015 | The Journal of Biomedical Research2015，29，4： | 2 |
| 3 | Enhancing Anisotropy Barriers of Dysprosium(III) Single‐Ion Magnets显示文摘 | Gong‐JunChen Yun‐NanGuo Jin‐LeiTian JinkuiTang WenGu XinLiu Shi‐PingYan PengCheng Dai‐ZhengLiao | 2012 | Chem. Eur. J2012，，9： | 1 |
| 4 | AUTOSIM:Automated Urban Traffic Operation Simulation via Meta-Learning显示文摘Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic management.It has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time system.To cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry attributes.Through a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal correlations.Besides,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a meta-learner.Through computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations. | Yuanqi Qin Wen Hua Junchen Jin Jun Ge Xingyuan Dai Lingxi Li Xiao Wang Fei-Yue Wang | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，9： | 0 |
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