Due to its significant contribution to global energy usage and the associated greenhouse
gas emissions, existing building stock's energy efficiency must improve. Predictive building …

As a cutting edge technology, Machine to Machine (M2M) communications are gaining
ground for managing and controlling M2M devices. Since these objects have intelligence, …

Fossil fuels serve a substantial fraction of global energy demand, and one major energy
consumer is the global building stock. In this work, we propose a framework to guide …

The contribution of this work is twofold: (1) We introduce a collection of ensemble methods for
time series forecasting to combine predictions from base models. We demonstrate insights …

Automated hyperparameter tuning aspires to facilitate the application of machine learning for
non-experts. In the literature, different optimization approaches are applied for that purpose…

In this emerging area article we review recent progress in the mechanical destruction of cancer
cells using laser-induced shock waves. The pure mechanical damaging and destruction …

The impact of pressure waves on cells may provide several possible applications in biology
and medicine including the direct killing of tumors, drug delivery or gene transfection. In this …

This paper analyzes the potential of knowledge discovery from sensed data, which enables
real-time systems monitoring, management, prediction and optimization in smart buildings. …

One of the key information pieces in improving energy efficiency of buildings is the appliance
level breakdown of energy consumption. Energy disaggregation is the process of obtaining …

Due to the demand for homogeneous, intelligent, and automated access to data measured
anywhere and from any device, Machine-to-Machine (M2M) platforms are evolving as globally…