Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …

Construction still accounts for a disproportionate number of injuries, inducing consequent
socioeconomic impacts. Despite recent attempts to improve construction safety by …

Most of the security threats in various communications networks are posed by the illegitimate
entities that enter or intrude within the network perimeter, which could commonly be termed …

Electricity is now the major form of energy used in residential buildings and has seen a
significant increase in usage over the past decades. One of the main features of electricity …

Purpose Project governance has been linked to project success because top management
support is necessary for projects to succeed. However, top managers are time poor and it is …

Objective While ample research exists about mother-child attachment, so far little focus has
been on specifics of father-child attachment. Even less research is available on the nature of …

An outlier in a pattern is dissimilar with rest of the pattern in a dataset. Outlier detection is an
important issue in data mining. It has been used to detect and remove anomalous objects …

In the last decade, a large amount of data from vehicle location sensors has been generated
due to the massification of GPS systems to track them. This is because these sensors usually …

Detecting outliers is a widely studied problem in many disciplines, including statistics, data
mining, and machine learning. All anomaly detection activities are aimed at identifying cases …

Vote-boosting is a sequential ensemble learning method in which the individual classifiers
are built on different weighted versions of the training data. To build a new classifier, the …