Showing 521 - 540 results of 2,307 for search '(( ct ((values decrease) OR (((largest decrease) OR (larger decrease)))) ) OR ( a large decrease ))', query time: 0.50s Refine Results
  1. 521

    The PL estimation result. by Zhendong Sun (4723221)

    Published 2025
    “…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
  2. 522

    Cox regression analysis results. by Zhendong Sun (4723221)

    Published 2025
    “…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
  3. 523

    Variable attributes. by Zhendong Sun (4723221)

    Published 2025
    “…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
  4. 524

    Vehicle arrival timing on short holidays. by Zhendong Sun (4723221)

    Published 2025
    “…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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  19. 539

    Knowledge and acceptance of COVID-19 vaccine. by Adaobi Uchenna Mosanya (20384248)

    Published 2024
    “…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”
  20. 540

    Logistics regression COVID-19 vaccine predictors. by Adaobi Uchenna Mosanya (20384248)

    Published 2024
    “…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”