
Junjie Liu
Articles
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Dec 6, 2024 |
mdpi.com | Junjie Liu |Xiaomeng Liu |Jiaoping Yang
1. IntroductionAccording to predictions of the United Nations, by 2025, 68% of the world’s population will reside in urban areas. The rapid pace of urbanization places immense pressure on urban infrastructure and services, including traffic congestion, energy shortages, housing deficits, aging infrastructure, inadequate healthcare, education challenges, and other issues [].
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Apr 30, 2024 |
mdpi.com | Xinrui Xu |Junjie Liu |Bo Wang |Jiaqi Wang
All articles published by MDPI are made immediately available worldwide under an open access license. No specialpermission is required to reuse all or part of the article published by MDPI, including figures and tables. Forarticles published under an open access Creative Common CC BY license, any part of the article may be reused withoutpermission provided that the original article is clearly cited. For more information, please refer tohttps://www.mdpi.com/openaccess.
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Feb 26, 2024 |
cell.com | Junjie Liu |Hong Kong Baptist |Duke Kunshan
Abstract In recent years, advancements in retinal image analysis, driven by machine learning and deep learning techniques, have enhanced disease detection and diagnosis through automated feature extraction. However, challenges persist, including limited dataset diversity due to privacy concerns and imbalanced sample pairs, hindering effective model training.
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Jul 29, 2023 |
mdpi.com | Junjie Liu |Nan Hu |Yao Jie Xie |Peng Wang
Abstract:Underwater adhesion involves bonding substrates in aqueous environments or wet surfaces, with applications in wound dressing, underwater repairs, and underwater soft robotics. In this study, we investigate the underwater adhesion properties of a polyacrylic acid hydrogel coated substrate. The underwater adhesion is facilitated through hydrogen bonds formed at the interface.
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May 19, 2023 |
onlinelibrary.wiley.com | Automation Tianjin |Zhao Xu |Junjie Liu |Yuehui Ji
Abstract Two distributed extended high-gain observers are studied for the generalized strict-feedback system in presence of external disturbance. The system state dynamics are reconstructed admissibly based on the limited measured output. First, a distributed high-gain observer is constructed to ensure the semiglobal ultimate uniform convergence of the state estimation error between the estimated state in each local observer and system state, for any prescribed initial system values.
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