Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Accessibility (1)
- Ad blockers (1)
- Adaptive technology (1)
- Blind (1)
- Blind users (1)
-
- Blindness (1)
- Crude oil (1)
- Crude oil prices (1)
- Dark patterns (1)
- Deceptive adverts (1)
- Deep learning (1)
- Econometrics (1)
- Ethical aspects (1)
- Extraneous content (1)
- False advertising (1)
- Machine learning (1)
- Multi-modal classification (1)
- Neural networks (1)
- Regression analysis (1)
- Screen readers (1)
- Securities markets (1)
- Software (1)
- Support vector machines (1)
- Technology application (1)
- Time series (1)
- Usability (1)
- Vision research (1)
- Visual impairment (1)
Articles 1 - 2 of 2
Full-Text Articles in Business
Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok
Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok
Computer Science Faculty Publications
Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …
A Hybrid Deep Learning Approach For Crude Oil Price Prediction, Hind Aldabagh, Xianrong Zheng, Ravi Mukkamala
A Hybrid Deep Learning Approach For Crude Oil Price Prediction, Hind Aldabagh, Xianrong Zheng, Ravi Mukkamala
Computer Science Faculty Publications
Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil price tends to fluctuate considerably during significant world events, such as the COVID-19 pandemic and geopolitical conflicts. In this paper, we propose a deep learning model for forecasting the crude oil price of one-step and multi-step ahead. The model extracts important features that impact crude oil prices and uses them to predict future prices. The prediction model …