Articles

  • Jun 18, 2024 | arxiv.org | Xiaowei Rose Luo

    arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

  • Nov 28, 2023 | mdpi.com | Jun Fu |Xiaowei Rose Luo |Zimin Xiao |Miaoping Lin

    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.

  • Nov 15, 2023 | mdpi.com | Jing Cheng |Xiaowei Rose Luo

    1. IntroductionA city is a gathering center for various industries, sectors, trades, and facilities. Different urban functions refer to the city’s role in a country or regional economic, political, and cultural life in a certain period. Urban functions are fundamental to a city, and they can reflect the unique characteristics of the city. The change or renewal of urban functions affects the development direction of a city.

  • Oct 9, 2023 | knowledge.insead.edu | Xiaowei Rose Luo

    Corporations often have a complicated relationship with the government. They strive to access state-controlled resources and influence policymaking by cultivating ties to officials. But if they are not careful, those very ties could make them vulnerable to political demands. To gain a net advantage, corporate strategists need a more sophisticated game.

  • Jul 25, 2023 | arxiv.org | Xiaowei Rose Luo

    Object detection has been widely applied for construction safety management, especially personal protective equipment (PPE) detection. Though the existing PPE detection models trained on conventional datasets have achieved excellent results, their performance dramatically declines in extreme construction conditions. A robust detection model NST-YOLOv5 is developed by combining the neural style transfer (NST) and YOLOv5 technologies.

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