Understanding the development of skills to command small unmanned aerial vehicle (sUAV) flight is key to sUAV adoption, and to the comprehension of educators and students' abilities. The aim of this research focuses on one potential factor in flight ability- whether the spatial perception of sUAV pilots plays a role in their ability to land on their targets. Within the literature, we currently assume that a pilot's landing ability and spatial perception are related. However, there is no data that directly supports nor proves the correlation between the two. Another factor that may play a role in the pilot's flight ability may be the user's visual perspective of the sUAV. We will be measuring users’ spatial perception through card rotation and cube comparison tests. Their ability to accurately land will be calculated based on the distance from the target landing compared to the actual landing coordinates of the sUAV. Other data such as the sUAV's take-off point or flight path will not be analyzed for this research project. Results will uncover the presence or absence of a correlation between spatial perception abilities and the ability to successfully land an sUAV on a given target. If there is a positive correlation, newer sUAV technology would be able to leverage autonomy that is adaptable to a user's manual operation and develop an ideal sUAV flight training program tailored to the use. A negative correlation will allow for the investigation of other factors that could contribute to a successful landing.

This paper seeks to examine what new potential engineers think about the effects of soft skills for their career. Research to date, while it has been helpful in exploring soft skills in general; it has not sought to discover what engineers in training, such as engineering students in university, actually think about the value of soft skills for their career. Through this research we hope to better understand: (1) How engineering students view soft skills, specifically, writing, presentation, conflict resolution, and creativity skills; (2) The extent to which there is a soft skill balance or imbalance across different engineering departments; (3) More effective ways to build soft skills of engineering students to prepare them for their work in industry. Our research design will utilize qualitative interview-based for data gathering, measurement and data analysis. We will gather data from interviews of third and fourth-year engineering students at a large Southwestern university, which will be digitally recorded, auto transcribed, and then analyzed by the researchers.

Individuals who are unable to communicate through speech rely on sign language to navigate the world. The problem that some run into is the miscommunication with those who do not understand sign language. Many technological advancements have permitted the creation of devices aimed at facilitating communication between those who do and do not understand sign language. These advancements include the use of Kinect cameras to capture movement, to the use of bend sensors. We propose a glove embedded with electroactive polymer stretch sensors (EAPS) worn by the signer whose movements will be captured by 3D software and translated into vocal English speech in real time. I plan to demonstrate improvements to glove-based sign language translation by implementing novel sensor types. The introduction of electroactive polymer sensors will result in the capturing of more range of motion from the glove system. These sensors are able to stretch along with the full motion of an individual’s fingers. This in turn will create a more accurate capturing of an individual’s sign gestures. The sensor’s sensitivity is also more precise which results in a more stable reading than the current prototype. Applying these recordings, the gloves will then output a vocal translation by communicating with a set database. These gestures will be cross referenced with the database and produce an auditory response. The result will be a glove system that actively translates ASL at the word level in real time.