The Words are not Enough: An Investigation into the Viability of Textual Complexity as a Feature for Recommendation Systems

Reading is an essential skill for any child to learn, and finding enjoyment in it can greatly contribute to developing proper reading comprehension. Finding the books they like could prove to be difficult. Utilizing collaborative filtering recommender systems to recommend books to children is a tricky task, the lack of user feedback makes it...

Evaluating the Performance of Different Models for Children’s Book Recommendations

Recently, a few children-centered recommendation systems have been created and evaluated. How- ever, these systems required user interaction to cre- ate ground truth to evaluate the result. This research aims to compare some of the traditional recommen- dation models and explore which trait could impact the recommendation process most for...

Impact of seismic wave length to detect high-magnitude earthquakes via deep learning

Earthquakes are one of the most destructive natural phenomena, both in terms of human lives, and property damage. Although they are treated as a random phenomenon, the ability to predict them, even few seconds before they occur, could be of great benefit to society. Lots of research has been done on this topic but without any significant results...

Impact of Focal Depth on Short-Term Earthquake Prediction using Deep Learning

Due to the devastating consequences of earthquakes, predicting their occurrence before the first strike has been a long standing research topic. Deep learning models have been used to facilitate prediction, using seismograph data to attempt to classify an earthquake right before it happens. However, this is a difficult task and research needs to...

Predicting Micro-Earthquakes with Deep Neural Networks

Earthquake prediction is the field of seismology concerned with predicting the time, location, and magnitude of earthquakes within a small time frame, usually defined in terms of minutes or seconds before an event. Such predictions can have a large impact on minimizing the damage caused by these seismic events, by providing early warnings to the...

A Comparative Study on Pseudo Random Number Generators in IoT devices

Pseudo-random number generators are the essential part of many security protocols such as signature schemes, key-exchange protocols and encryption algorithms. The security of these protocols is usually dependent on the quality of the generators they use. The generation of unpredictable random numbers supplies refreshment to the protocols, which...

A Comparative Study on Lightweight Authentication Protocols for IoT

Wireless Sensor Networks(WSN's) are networks of sensor that wirelessly communicate to each other. The communication of these sensors needs to be secured to prevent leaking of potentially sensitive information of the data sent between the user, gateway and sensors. For WSN's lightweight authentication, protocols have been developed in order to...