Technological advances and the emergence of the Internet of Things have lead to the
collection of vast amounts of scientific data from increasingly powerful scientific instruments …

The insufficiency of current energy sources, elevated costs and global climate worriment are
distinctive factors making of renewable energy an issue of boosting consideration. In this …

Golf courses can be considered as precision agriculture, as being a playing surface, their
appearance is of vital importance. Areas with good weather tend to have low rainfall …

The overview presents the development and application of Hierarchical Temporal Memory
(HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in …

Anomaly detection in time series is a well-studied subject, and it is well-documented in the
literature such as ECG signal. Many successful algorithms for analyzing ECG signals are …

Deep learning is on the rise in the machine learning community, because the traditional
shallow learning architectures have proved unfit for the more challenging tasks of machine …

Predictive coding (PDC) has recently attracted attention in the neuroscience and computing
community as a candidate unifying paradigm for neuronal studies and artificial neural …

The difference in electricity and power usage time leads to an unbalanced current among
the three phases in the power grid. The three-phase unbalanced is closely related to power …

HTM-MAT is a MATLAB based toolbox for implementing cortical learning algorithms (CLA)
including related cortical-like algorithms that possesses spatiotemporal properties. CLA is a …

The recent development in the theory of Hierarchical Temporal Memory (HTM)-Cortical
Learning Algorithms (CLA) which models the structural and algorithmic properties of …