This dataset includes  the Channels Switch Sequences of 300 IPTV viewers in Guangzhou, P.R. China, in Augest, 2014.

There are 4 columns in the file, which represent viewer ID, the current channel number, th next channel number, the date of the month, respectively.

The first column, the ID code of a viewter, ranks with the times the viewer watched tv channels. The more times a viewer watches tv channels, the bigger

the ID is. In a day, the rows are time series and generated step by step as the real watching tv behavior. 

The system obtained interference information from the measurement signal, solved the problem of phase wrapping, and got the accurate coordinates of target. The tags and tag-free items including shrimp chips, cola and instant noodles were taken as target respectively in experiment.

This repository aims to publish a sEMG database for hand gesture recongnition, which is suitable for intra-session, inter-session, inter-day and inter-subject tests. Six subjects were involved in data collection on ten days, and two sessions a day with the interval of half an hour. In each session, one trial (10 secondes) for each geature was conducted. The electrode sleeve did not reweared between two sessions in a day. The utilised sEMG device was customised by the Intelligent System and Biomedical Robotics Group, which was discussed in [1]. 

Machine learning is becoming increasingly important for companies and the scientific community. It allows us to generate solutions for several problems faced by society. In this study, we perform a science mapping analysis on the machine learning research, in order to provide an overview of the scientific work during the last decade in this area and to show trends that could be the basis for future developments in the field of computer science. This study was carried out using the CiteSpace and SciMAT tools based on results from Scopus and Clarivate Web of Science.