Browsing by Author "Wang, Xinyu"

Now showing 1 - 2 of 2
  • Thumbnail Image
    DiLogics: Creating Web Automation Programs with Diverse Logics
    Pu, Kevin; Yang, Jim; Yuan, Angel; Ma, Minyi; Dong, Rui; Wang, Xinyu; Chen, Yan; Grossman, Tovi (ACM, 2023-10-29)
    Knowledge workers frequently encounter repetitive web data entry tasks, like updating records or placing orders. Web automation increases productivity, but translating tasks to web actions accurately and extending to new specifications is challenging. Existing tools can automate tasks that perform the same logical trace of UI actions (e.g., input text in each field in order), but do not support tasks requiring different executions based on varied input conditions.We present DiLogics, a programming-by-demonstration system that utilizes NLP to assist users in creating web automation programs that handle diverse specifications. DiLogics first semantically segments input data to structured task steps. By recording user demonstrations for each step, DiLogics generalizes the web macros to novel but semantically similar task requirements. Our evaluation showed that non-experts can effectively use DiLogics to create automation programs that fulfill diverse input instructions. DiLogics provides an efficient, intuitive, and expressive method for developing web automation programs satisfying diverse specifications.
  • Thumbnail Image
    A Systematic Review of the Scientific Literature on Pollutant Removal from Stormwater Runoff from Vacant Urban Lands
    Wang, Yang; Yin, Hao; Liu, Zhiruo; Wang, Xinyu (MDPI, 2022-10-10)
    Even though the common acknowledgment that vacant urban lands (VUL) can play a positive role in improving stormwater management, little synthesized literature is focused on understanding how VUL can take advantage of different stormwater control measures (SCMs) to advance urban water quality. The project aims to provide urban planners with information on the remediation of vacant lands using urban runoff pollutant removal techniques. To find the most effective removal method, relevant scholarly papers and case studies are reviewed to see what types of vacant land have many urban runoff pollutants and how to effectively remove contaminants from stormwater runoff in the city by SCMs. The results show that previously developed/used land (but now vacant) has been identified as contaminated sites, including prior residential, commercial, industrial, and parking lot land use from urban areas. SCMs are effective management approaches to reduce nonpoint source pollution problems runoff. It is an umbrella concept that can be used to capture nature-based, cost-effective, and eco-friendly treatment technologies and redevelopment strategies that are socially inclusive, economically viable, and with good public acceptance. Among these removal techniques, a bioretention system tends to be effective for removing dissolved and particulate components of heavy metals and phosphorus. Using different plant species and increasing filter media depth has identified the effectiveness of eliminating nitrate nitrogen (NO3-N). A medium with a high hydraulic conductivity covers an existing medium with low hydraulic conductivity, and the result will be a higher and more effective decrease for phosphorus (P) pollutants. In addition, wet ponds were found to be highly effective at removing polycyclic aromatic hydrocarbons, with removal rates as high as 99%. For the removal of perfluoroalkyl acid (PFAA) pollutants, despite the implementation of SCMs in urban areas to remove PFAAs and particulate-related contaminants in stormwater runoff, the current literature has little information on SCMs’ removal of PFAAs. Studies have also found that VUL’s size, shape, and connectivity are significantly inversely correlated with the reduction in stormwater runoff. This paper will help planners and landscape designers make efficient decisions around removing pollutants from VUL stormwater runoff, leading to better use of these spaces.