Julia Ann Jose

HC
3papers
2citations
Novelty15%
AI Score12

3 Papers

HCOct 12, 2021
Inclusive Design: Accessibility Settings for People with Cognitive Disabilities

Trae Waggoner, Julia Ann Jose, Ashwin Nair et al.

The advancement of technology has progressed faster than any other field in the world and with the development of these new technologies, it is important to make sure that these tools can be used by everyone, including people with disabilities. Accessibility options in computing devices help ensure that everyone has the same access to advanced technologies. Unfortunately, for those who require more unique and sometimes challenging accommodations, such as people with Amyotrophic lateral sclerosis ( ALS), the most commonly used accessibility features are simply not enough. While assistive technology for those with ALS does exist, it requires multiple peripheral devices that can become quite expensive collectively. The purpose of this paper is to suggest a more affordable and readily available option for ALS assistive technology that can be implemented on a smartphone or tablet.

SIOct 12, 2021
BotNet Detection on Social Media

Aniket Chandrakant Devle, Julia Ann Jose, Abhay Shrinivas Saraswathula et al.

As our reliance on social media platforms and web services increase day by day, exploiters view these platforms as an opportunity to manipulate our thoughts ad actions. These platforms have become an open playground for social bot accounts. Social bots not only learn human conversations, manners, and presence but also manipulate public opinion, act as scammers, manipulate stock markets, and so on. There has been evidence of bots manipulating people's opinions and thoughts which can be a great threat to democracy. Identification and prevention of such campaigns that release or create these bots have become critical. Our goal in this paper is to leverage web mining techniques to help detect fake bots on social media platforms such as Twitter, thereby mitigating the spread of disinformation.

OTJan 4, 2021
Continuous Glucose Monitoring Prediction

Julia Ann Jose, Trae Waggoner, Sudarsan Manikandan

Diabetes is one of the deadliest diseases in the world and affects nearly 10 percent of the global adult population. Fortunately, powerful new technologies allow for a consistent and reliable treatment plan for people with diabetes. One major development is a system called continuous blood glucose monitoring (CGM). In this review, we look at three different continuous meal detection algorithms that were developed using given CGM data from patients with diabetes. From this analysis, an initial meal prediction algorithm was also developed utilizing these methods.