Browsing by Subject "Data Collection"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Cook County and Grand Marais Energy Conservation and Renewable Energy Plan Appendices(2012) Cook CountyThis is a series of annexes to the final report, and containing the following materials: Public Survey Results (Powerpoint presentation); Energy Toolbox Resources; Biomass Phase I Report Executive Summary; and Wind Feasibility Study. As noted in the previous document, there is little mention of water resources.Item Critical issues in researching domestic violence among people of color with disabilities(Journal of Aggression, Maltreatment and Trauma, 2009-01) Elizabeth, Lightfoot; Williams, Oliver J.While there are a number of programs emerging providing services to people of color with disabilities who experience domestic violence, there is little research on the needs of this population. Using data collected from two national focus groups of nineteen expert informants, this article outlines key areas of research needed for providing better services to people of color who are Deaf or have disabilities, and appropriate research methods for collecting data with this population. Respondents indicated that a research agenda should include investigating the scope of the problem, in-depth needs of domestic violence survivors, cost-effectiveness of culturally and disability specific programs, and development of best practices through in-depth evaluations of existing programs.Item Masked Faces in Context (MASON) for Masked Face Detection and Classification(2023-01) Shield, HelenaAs the SARS-CoV-2 virus mutated and spread around the world, scientists andpublic health officials were faced with the responsibility of making health recommen- dations as they studied the novel disease in real time. One such recommendation was the use of face masks of varying types as a method of reducing disease spread in public spaces. Evaluating the effectiveness of such measures requires accurate data collection of the proper facemask usage. The use of computer vision models to detect and clas- sify face mask usage can aid in the collection process by monitoring usage in public spaces. However, training these models requires accurate and representative datasets. Pre-COVID-19 datasets and synthetic datasets have limitations that affect the accu- racy of models in real world settings such as inaccurate representations of occlusion and limited variety of subjects, settings, and masks. In this work we present a new dataset Masked Faces in Context (MASON) of annotated real-world images focusing on the time period of 2020 to the present and baseline detection and classification models that outperforms the current state of the art. This dataset better snapshots mask wearing under covid with greater representation of different age groups, mask types, common occlusion items such as face shields, and face position. Our experiments demonstrate increased accuracy in face mask detection and classification.