Výsledky vyhledávání

A Dual-Polarized Planar Ultrawideband Phased Array Antenna with Ultra-Low Profile

Autor: Linkai Yang, Shiwei Qu

Publikováno v: 2022 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ffaa547ab1c2a4c38091f4d79ac02675
https://doi.org/10.1109/imws-amp54652.2022.10106913

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Adaptive CCR-ELM with variable-length brain storm optimization algorithm for class-imbalance learning

Autor: Shi Cheng, Jian Cheng, Linkai Yang, Pei Zhang, Chen Jingjing, Yi-nan Guo

Publikováno v: Natural Computing. 20:11-22

Class-specific cost regulation extreme learning machine (CCR-ELM) can effectively deal with the class imbalance problems. However, its key parameters, including the number of hidden nodes, the input weights, the biases and the tradeoff factors are no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6e0071cfedb64bd3ae1ab17dc4d74f25
https://doi.org/10.1007/s11047-019-09735-9

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PAX2 promotes epithelial ovarian cancer progression involving fatty acid metabolic reprogramming

Autor: Qi Wang, Barbara C. Vanderhyden, De-Sheng Yao, Yingzhao Liu, Yannan Mao, Linkai Yang, Yong Tang, Yan Feng, Kenneth Garson

Publikováno v: International Journal of Oncology

Ovarian cancer is the fifth most common type of cancer afflicting women and frequently presents at a late stage with a poor prognosis. While paired box 2 (PAX2) expression is frequently lost in high‑grade serous ovarian cancer, it is expressed in a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22815fac65e61a8a84c00317dce0ad61
https://doi.org/10.3892/ijo.2020.4958

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Manifold cluster-based evolutionary ensemble imbalance learning

Autor: Jiawei Feng, Yi-nan Guo, Zekuan Yu, Hui Lu, Linkai Yang, Botao Jiao

Publikováno v: Computers & Industrial Engineering. 159:107523

For an imbalanced dataset, traditional machine learning methods usually misclassify minority samples due to the indicator evaluating classification accuracy biased toward majority class. To address the issue, manifold cluster-based evolutionary ensem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d177a1e72db4fffbd3d999dd10744d0
https://doi.org/10.1016/j.cie.2021.107523

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