Responsible, efficient and environmentally aware energy consumption behavior is
becoming a necessity for the reliable modern electricity grid. In this paper, we present an …

Nowadays, there is an ever-increasing migration of people to urban areas. Health care
service is one of the most challenging aspects that is greatly affected by the vast influx of …

With the proliferation of smart meters in smart grids, new challenges have emerged in the
energy sector and applications are continuously developed, mainly concerning data …

Demand-response (DR) and energy savings programs are tailored based on users'
electricity consumption patterns, discovered from the smart meter data, but do not …

A polar projection-based algorithm is proposed to reduce the computational complexity
associated with dimension reduction in unsupervised learning. This algorithm employs K …

As the adoption rate of commercial smart home solutions increases, it drives the
development of novel system features, needed to support advanced user scenarios. Being …

In the Internet of Energy (IoE) ecosystem, an accurate electricity load forecasting is critically
important to all the participants in the smart grids, such as manufacturers, utility companies …

Rapid evolution of sensing technology and increasing power computation has resulted in
the emergence of smart environments with smart health services. Smart environments can …

Autonomy and adaptability are essential components of ambient intelligence. For example,
in smart homes, proactive acting and occupants advising, adapted to current and future …

In the contemporary trading environment any competitive advantage is of core interest to
technical traders and financial analysts. Motifs (ie time series patterns corresponding to …