Selected School works
Selected School works
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Capstone poster.pdfWorkforce needs of STEM employers in South Side of Chicago and the resource gap - Capstone
South Side of Chicago has a higher unemployment rate and lower income level compared to other sides of the Chicago city. To help the job seekers find a job in their neighborhood with satisfied salary, a survey is conducted by Argonne lab to learn the STEM (Science, Technology, Engineer, and Math) employers' needs.
My capstone is based on the survey data from my internship with Argonne. After analyzing the employers' needs and the workforce training provided by Chicago city, I identified that the city lack both South Side - focused and industry-specific programs.
How do socioeconomic factors affect travel mode choices in the core of South Side Chicago?
This study examines the relationship between five socioeconomic fators and the travel mode choice in nine neighborhoods of the South Side Chicago. By runing multinomial models in R studio, the study shows that the travel mode choices are diverse across industries. The result suggests that to encourage people use more alternative travel modes, strategies focusing on industries could be a possible approach.
The data source is CAMP-My Daily Travel Survey.
Travel Demand Model and Forecast in Champaign-Urbana: Urban Sprawling Senario
This project predicts future travel demand in Champaign-Urbana in 2040. Based on the baseline scenario 2010, we predicted the employment oppotunities and population for: Business-As-Usual (BAU) 2040 and Urban Sprawl 2040.
After runing travel demand models for three senarios in CUBE, we found that the Urban Sprawling scenario will have more congestion and some roads will be severly affected. We recommended to add more bus lines to those areas to avoid congestion and improve the connectivity.
The data source is CUUATs 2040.
The impact of student and race on poverty level in Champaign-Urbana
As a college town, Champaign-Urbana has a high poverty rate. This project studies does college students and race have an impact on the poverty level. By calculating the weighted mean center in GIS, I found that college students do have a strong impact on poverty rates, and more significant on the neighborhoods that near campus. The disparity between the distribution of race and income shows that the race and income are related, and the linear relationship confirms this finding.
The data source is ACS 5-year 2020.
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