Biblio

In this fast-running world, machine communication plays a vital role. To compete with this world, human-machine interaction is a necessary thing. To enhance this, Natural Language Processing technique is used widely. Using this technique, we can reduce the interaction gap between the machine and human. Till now, many such applications are developed which are using this technique.This tool deals with the various methods which are used for development of grammar error correction. These methods include rule-based method, classifier-based method and machine translation-based method. Also, models regarding the Natural Language Processing (NLP) pipeline are trained and implemented in this project accordingly. Additionally, the tool can also perform speech to text operation.

In this paper, a transformer model has been developed. The model is based on the equivalent electrical circuit used in transient simulation studies which considers the non-linearity of the iron core. The non-linear ferromagnetic behavior of the iron core was obtained by using the Jiles-Atherton hysteresis model. The magnetizing inrush current of a core type single-phase transformer was analyzed under four different energization conditions. The primary winding of the transformer was connected to the supply at various instants while there was either some level of remanent flux or no remanent flux in the iron core. Corresponding simulation results are presented and discussed.