Extreme Learning Machine (ELM) is popular in batch learning, sequential and progressive due to its speed, easy integration, generalization ability. While, Traditional ELM cannot train massive data rapidly efficiently memory residence, high time space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there no certainty that arrangement weights biase...

This paper explores the relationship between unsupervised machine learning models, and mental models of those who develop or use them. In particular, we consider as well ‘organisational co-learning process’ that creates them, affordances. The process involves inputs originating both from human participants’ shared semantics, data. By combining these, resulting computational afford a newly shape...

The COVID-19 pandemic has been one of the most challenging crises attacking world in last three years. Many systems have introduced field detection.
 In this research, machine learning and deep models for detection with a probability presence are proposed. scenario, dataset is split into 70% training 30% testing, segmentation process applied to CT images order get lung ROI only. features t...