Artificial Intelligence

This dataset is shared for capacitor C and ESR estimation using convolution neural network. The dataset is collected in a experimental modular moultilevel converter, which includes the capacitor voltage at low and medium frequency band, and the arm current. Wavelet transform is used to transfer the time series data to images, which present the inherent data features to image patterns. In a degraded capacitor, the C decreases and the ESR increases, which result in different image patterns.

In today’s world, deaf and mute person face many problems in their daily life due to miscommunication as well as misunderstanding. These problems have existed since long ago but are ultimately being solved with the introduction of Hand sign language. There exist many different sign languages such as ASL, ISL, etc. But for regional and low-resource languages like Mizo, the state language of Mizoram, spoken by the northeastern people in India, not much research has been done on the advancement of sign language based on the Mizo language.

This large dataset includes six small datasets, including two types, one contains the original node relationship information and node feature information, please use it through the common network construction methods; the other is the dataset which has been processed, including the direct edge information and node's association information, which can be used to construct the network directly through the network construction methods.

Translated with www.DeepL.com/Translator (free version)

The data set is from the Case Western Reserve University Rolling Bearing data set. SK6205 bearing located at the drive end is selected as the research object, and the acquisition frequency is 12KHz. The fault type is divided into three types, namely inner ring fault, rolling body fault and outer ring fault, and each fault type is divided into three fault sizes: 0.007, 0.014 and 0.021 inches.The length of each sample is 1024 and the repetition rate is 50%