One of the opening steps towards obtaining a reasoned analysis is the detection of outlaying
observations. Even if outliers are often considered as a miscalculation or noise, they may …

Abstract Information and Communication Technology (ICT) has a great impact on social
wellbeing, economic growth and national security in todays world. Generally, ICT includes …

Anomaly detection is an important data analysis task. It is used to identify interesting and
emerging patterns, trends and anomalies from data. Anomaly detection is an important tool …

Outlier detection is an important data analysis task in its own right and removing the outliers
from clusters can improve the clustering accuracy. In this paper, we extend the k-means …

The Internet of Things (IoT) is a fact today where a high number of nodes are used for
various applications. From small home networks to large-scale networks, the aim is the …

Fraud entails deception in order to obtain illegal gains; thus, it is mainly evidenced within
financial institutions and is a matter of general interest. The problem is particularly complex …

This paper provides a comprehensive survey of anomaly detection for the Internet of Things
(IoT). Anomaly detection poses numerous challenges in IoT, with broad applications …

The accurate estimation of nearshore bathymetry is necessary for multiple aspects of coastal
research and practices. The traditional shipborne single-beam/multi-beam echo sounders …

Outliers has been studied in a variety of domains including Big Data, High dimensional data,
Uncertain data, Time Series data, Biological data, etc. In majority of the sample datasets …

Fuzzy clustering is a well-established technique among the well-known clustering
techniques in several real-world applications due to easy implementation and produces …