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The route to tenure is often clear and well-defined, while the path to full professor is notoriously described as ambiguous and elusive, which raises questions and uncertainty on how to be promoted. In order to explore institutional concerns expressed by associate professor women in science, technology, engineering, and mathematics (STEM) and social and behavioral sciences (SBS) regarding the pathway to full professor, interviews were conducted with members of the Belayers Network at the University of Colorado Colorado Springs (UCCS). The Belayers Network consists of STEM and SBS associate professor women and is designed to support their promotion to full professor through opportunities to come together for informational, tangible, and emotional resources. An instrumental case study with a pragmatic theoretical lens was employed for this study. Interviews were analyzed inductively and resulted in five themes: (1) Full professor promotion criteria are ambiguous; (2) Teaching and service expectations are too high; (3) Lack of research collaborators inhibits scholarly output; (4) Scarce research-related resources are a persistent struggle; and (5) Mentoring and support are absent. The academy may find it instructive to understand better associate professor women’s institutional concerns about the pathway to full professor and possible ways to offset the obstacles toward achievement. Additionally, pragmatic solutions and implications are offered to mitigate these concerns in the context of UCCS. This research is sponsored by a National Science Foundation ADVANCE Adaptation Award. 

Reliable lane-following is one of the most important tasks for an automated vehicle or ADAS. The intent of this project was to design and evaluate multiple lane-following algorithms for an automated vehicle using computer vision. The implemented algorithms' performance was then evaluated on a testing course and compared with a human driver. ROS and OpenCV were used to detect and follow lanes on the road. A street-legal vehicle with a high-definition camera and drive-by-wire system was used to implement and evaluate driving data. Each algorithm was evaluated based on time for completion, speed limit infractions, and lane positioning infractions. The recorded evaluation data determined the most reliable lane-following algorithm. All of our algorithms had a success rate of at least 60% on certain lanes of the testing course.