Mild Cognitive Impairment (MCI) often occurs prior to the more serious condition of dementia and early detection of MCI is an important but challenging task because of its indistinct symptoms. Work has been done developing ...

Computer Security covers a wide array of topics, with much of the development in the field happening outside academia. We look at intrusion detection, and evaluate the effectiveness of machine learning in the development ...

The cognitive radio-based wireless networks have been proposed as a promising technology to improve the utilization of the radio spectrum through opportunistic spectrum access. In this context, the cognitive radios ...

In commercial beekeeping, monitoring the apiaries is difficult as they are often spread over large distances. Building a vision-based hive monitoring system is a promising—albeit difficult—solution to this problem. In this ...

High-dimensional data has always been a serious problem especially when the dataset has many irrelevant attributes. With the advancement of internet and cloud computing platforms, an exceptional rise has been recorded in ...

An unsupervised deep anomaly detection system is implemented to augment the water quality monitoring system used at a recirculating aquaculture system (RAS) facility. Its purpose is to increase the system’s anomaly detection ...

Wind turbine power curve modeling plays an important role in wind energy management. Accurate estimation of power curves can help reducing power systems maintenance costs. In this thesis, we use machine learning techniques ...

Electromagnetic imaging is a method that aims to reconstruct a spatial map of the material properties of a target through non-invasive measurements, allowing an observer to see inside objects, such as the human body, ...

In today’s world, detection of malware is a prevalent challenge due to the evolving nature of malware designs and techniques. Many machine learning algorithms, such as ANNs, use supervised learning, which relies on a labeled ...