Výsledky vyhledávání - "Qingmei Zhou"

Akademický článek

The impact of China’s new Environmental Protection Law on corporate environmental investments

Autor: Weiming Liu, Yating Qiu, Lijiang Jia, You Wu, Qingmei Zhou

Publikováno v: Frontiers in Energy Research, Vol 11 (2023)

As an important lever for China’s green development strategy, whether the new Environmental Protection Law can effectively form investment incentives for enterprises has attracted much attention and is also an important topic that theoretical resea

Externí odkaz: https://doaj.org/article/b2302ffa74af474cbce0b42b916a839a

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Akademický článek

Broad Learning Model Based on Enhanced Features Learning

Autor: Qingmei Zhou, Xiping He

Publikováno v: IEEE Access, Vol 7, Pp 42536-42550 (2019)

With the continuous development of deep learning, its drawbacks are also beginning to appear. As an alternative to deep learning, broad learning is emerging. However, the level of broad learning model is shallow, so feature learning is not sufficient

Externí odkaz: https://doaj.org/article/b92a24b276fe44df996eb2c601906852

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Akademický článek

Existence and multiplicity of solutions for p(x)-Laplacian equations in R^N

Autor: Bin Ge, Qingmei Zhou

Publikováno v: Electronic Journal of Differential Equations, Vol 2014, Iss 133,, Pp 1-8 (2014)

This article concerns the existence and multiplicity of solutions to a class of p(x)-Laplacian equations. We introduce a revised Ambrosetti-Rabinowitz condition, and show that the problem has a nontrivial solution and infinitely many solutions.

Externí odkaz: https://doaj.org/article/8a4d1d844dd749fbb52372f59e8a37c2

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Top-N Recommendation Using Low-Rank Matrix Completion and Spectral Clustering

Autor: Qingmei Zhou, Wei Zhao, Xuangou Wu, Qian Wang, Xun Shao

Publikováno v: IEICE Transactions on Communications. :951-959

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::41221fa53bd3748af6dc17cf80191676
https://doi.org/10.1587/transcom.2019ebp3230

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LncRNA PAXIP1-AS1 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Ovarian Cancer

Autor: Buze Chen, Guilin Li, Qingmei Zhou, Qing Chen, Si-Yan Zhu, Xiaoyuan Lu, Hui Liu

Background: The long non-coding RNA (LncRNA) PAXIP1 antisense RNA 1 (PAXIP1-AS1) was found to promote proliferation, migration, EMT, and apoptosis of ovarian cancer (OC) cells in OC cell lines, but the relationship between PAXIP1-AS1 expression and c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::868a856a4f26f4279b6f1d4b640d2c42
https://doi.org/10.21203/rs.3.rs-1018252/v1

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Network Pharmacology, Integrated Bioinformatics, and Molecular Docking Reveals the Anti-Ovarian Cancer Molecular Mechanisms of Cinnamon (Cinnamomum cassia (L.) J. Presl)

Autor: Buze Chen, Xin Jin, Haihong Wang, Qingmei Zhou, Guilin Li, Xiaoyuan Lu

Publikováno v: Natural Product Communications. 17:1934578X2211191

Cinnamon ( Cinnamomum cassia (L.) J. Presl) is a popular natural spice with various pharmacological properties. This study was based on network pharmacology integrating bioinformatics and molecular docking to explore the potential molecular mechanism

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::03d51f62839e889ab9ebf17fefea6d62
https://doi.org/10.1177/1934578x221119118

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Spectral Clustering-based Matrix Completion Method for Top-n Recommendation

Autor: Qingmei Zhou, Jiuya Zhang, Xin Chen

Publikováno v: Proceedings of the 2019 5th International Conference on Computing and Data Engineering.

In the era of big data on the Internet, top-N recommender systems constitute a mission-critical technology in e-commerce applications. However, sparse data is one of the key factors leading to poor performance of the recommendation algorithm. In this

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::006d26df290a6899a89870cec12e1573
https://doi.org/10.1145/3330530.3330531

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An approach for monitoring sand mining based on sound feature

Autor: Xiping He, Qingmei Zhou

Publikováno v: IOP Conference Series: Materials Science and Engineering. 806:012052

In order to strengthen the management of sand excavation in river courses and prevent the occurrence of illegal sand mining activities, this paper proposes an approach for monitoring sand mining based on sound. Firstly, Mel Frequency Cepstral Coeffic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9e6d11e3c98b397a0379d32dbfd8be71
https://doi.org/10.1088/1757-899x/806/1/012052

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