Mengshuang Liu
Biographic Data
| ID | 7184779 |
|---|---|
| NAME | Mengshuang Liu |
| GIVEN NAMES | Mengshuang |
| FAMILY NAME | Liu |
| SIGNATURE | LIU M |
| AFFILIATIONS | Liaocheng University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places
Background People usually spend most of their time indoors, so indoor fine particulate matter (PM 2.5 ) concentrations are crucial for refining individual PM 2.5 exposure evaluation. The development of indoor PM 2.5 concentration prediction models is essential for the health risk assessment of PM 2.5 in epidemiological studies involving large populations. Methods In this study, based on the monitoring data of multiple types of places, the classic…
Coworker feedback seeking and feedback environment in China
We empirically explored the impact of feedback seeking, including feedback inquiry and monitoring, on the coworker feedback environment via coworker identification. Participants were 264 employees who worked in research and development, design, and technology sectors of industrial enterprises in China. The results indicated that feedback monitoring, feedback inquiry, and coworker identification were all positively related to the coworker feedback…
No prominent works on this page.
Coworker feedback seeking and feedback environment in China
We empirically explored the impact of feedback seeking, including feedback inquiry and monitoring, on the coworker feedback environment via coworker identification. Participants were 264 employees who worked in research and development, design, and technology sectors of industrial enterprises in China. The results indicated that feedback monitoring, feedback inquiry, and coworker identification were all positively related to the coworker feedback…
Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places
Background People usually spend most of their time indoors, so indoor fine particulate matter (PM 2.5 ) concentrations are crucial for refining individual PM 2.5 exposure evaluation. The development of indoor PM 2.5 concentration prediction models is essential for the health risk assessment of PM 2.5 in epidemiological studies involving large populations. Methods In this study, based on the monitoring data of multiple types of places, the classic…
Computer Science (2 works) · Air Quality and Health Impacts (1 works) · Air Quality Monitoring and Forecasting (1 works) · China (1 works) · Engineering (1 works) · Environmental Science (1 works) · Evaluation of Teaching Practices (1 works) · Feedback loop (1 works) · Geography (1 works) · Identification (biology (1 works)