Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

A time-frequency diagram is a commonly used visualization for observing the time-frequency
distribution of radio signals and analyzing their time-varying patterns of communication …

The increasing popularity of micro-scale power-scavenging techniques for wireless sensor
networks (WSNs) is paving the way to energy-autonomous sensing systems. To sustain …

Pattern discovery from time series is of fundamental importance. Particularly when the
domain expert derived patterns do not exist or are not complete, an algorithm to discover …

For many years, how to make stock market predictions has been a prevalent research topic.
To carry out accurate forecasting, stock analysts and academic researchers have tried …

The expected huge increase in the number of IoT data sources (sensors, embedded
systems, personal devices etc.) will give rise to network-edge computing, ie, data pre …

An automatic stock market categorization system would be invaluable to individual investors
and financial experts, providing them with the opportunity to predict the stock price changes …

Time series data, due to their numerical and continuous nature, are difficult to process,
analyze, and mine. However, these tasks become easier when the data can be transformed …

One of the major duties of financial analysts is technical analysis. It is necessary to locate the
technical patterns in the stock price movement charts to analyze the market behavior …