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- All Subjects: deep learning
- All Subjects: Entrepreneurship
- Creators: Computer Science and Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
When examining the average college campus, it becomes obvious that students feel rushed from one place to another as they try to participate in class, clubs, and extracurricular activities. One way that students can feel more comfortable and relaxed around campus is to introduce the aspect of gaming. Studies show that “Moderate videogame play has been found to contribute to emotional stability” (Jones, 2014). This demonstrates that the stress of college can be mitigated by introducing the ability to interact with video games. This same concept has been applied in the workplace, where studies have shown that “Gaming principles such as challenges, competition, rewards and personalization keep employees engaged and learning” (Clark, 2020). This means that if we manage to gamify the college experience, students will be more engaged which will increase and stabilize the retention rate of colleges which utilize this type of experience. Gaming allows students to connect with their peers in a casual environment while also allowing them to find resources around campus and find new places to eat and relax. We plan to gamify the college experience by introducing augmented reality in the form of an app. Augmented reality is “. . . a technology that combines virtual information with the real world” (Chen, 2019). College students will be able to utilize the resources and amenities available to them on campus while completing quests that help them within the application. This demonstrates the ability for video games to engage students using artificial tasks but real actions and experiences which help them feel more connected to campus. Our Founders Lab team has developed and tested an AR application that can be used to connect students with their campus and the resources available to them.
Obesity rates among adults have steadily grown in recent decades all the way up to<br/>42.4% in 2018. This is a 12% increase from the turn of the century (Center for Disease Control<br/>and Prevention, 2021). A major reason for this rise is increased consumption of processed,<br/>high-calorie foods. People eat these foods at a young age and develop bad eating habits that can<br/>last for the rest of their lives. It is essential to intervene early and help adolescents form<br/>balanced, healthy eating habits before bad habits are already formed. Our solution to this<br/>problem is Green Gamers. Green Gamers combines adolescent’s passion for gaming with<br/>healthy eating via in-game rewards for healthy eating. People will be able to purchase healthy<br/>food items, such as a bag of carrots, and on the packaging there will be a QR code. They will<br/>then be able to scan the code on our website, and earn points which will unlock in-game items<br/>and other rewards. Video game rewards act as effective motivators for you people to eat more<br/>healthy foods. After the solution was formulated, a preliminary survey was conducted to<br/>confirm that video game related rewards would inspire children to eat more healthy foods.<br/>Based on those results, we are currently in the process of running a secondary market research<br/>campaign to learn if gift card rewards are a stronger motivator. Our end goal for Green Gamers<br/>would be to partner with large gaming studios and food producers. This would allow us access to<br/>many gaming franchises, so that rewards are available from a wide variety of games: making the<br/>platform appealing to a diverse audience of gamers. Similarly, a relationship with large food<br/>producers would give us the ability to place QR codes on a greater assortment of healthy food<br/>items. Although no relationships with large companies have been forged yet, we plan to utilize<br/>funding to test our concept on small focus groups in schools
algorithms for recommending new music to users. However, at the
core of their recommendations is the collaborative filtering algorithm,
which recommends music based on what other people with similar
tastes have listened to [1]. While this can produce highly relevant
content recommendations, it tends to promote only popular content
[2]. The popularity bias inherent in collaborative-filtering based
systems can overlook music that fits a user’s taste, simply because
nobody else is listening to it. One possible solution to this problem is
to recommend music based on features of the music itself, and
recommend songs which have similar features. Here, a method for
extracting high-level features representing the mood of a song is
presented, with the aim of tailoring music recommendations to an
individual's mood, and providing music recommendations with
diversity in popularity.
This thesis is part of a collaboration between ASU’s Interactive Robotics Laboratory and NASA’s Jet Propulsion Laboratory. In this thesis, the training pipeline from Sharma’s paper “Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks” was modified to perform pose estimation on a complex object - specifically, a segment of a hollow truss. After initial attempts to replicate the architecture used in the paper and train solely on synthetic images, a combination of synthetic dataset generation and transfer learning on an ImageNet-pretrained AlexNet model was implemented to mitigate the difficulty of gathering large amounts of real-world data. Experimentation with pose estimation accuracy and hyperparameters of the model resulted in gradual test accuracy improvement, and future work is suggested to improve pose estimation for complex objects with some form of rotational symmetry.