Abstract Maritime Autonomous Surface Ships are in the development stage and they play an important role upcoming future. Present generation ships semi-autonomous controlled by ship crew. The performance of is predicted using data collected from with help machine learning deep methods. Path planning for autonomous necessary estimating best possible route minimum travel time it depends on weather...

Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) are two frameworks which operationalize depth of processing of a vocabulary learning task. However, there is dearth of research comparing the predictive power of the ILH and the TFA across second language (L2) vocabulary learning tasks. The present study, therefore, aimed to examine this issue across four vocabulary learning...

Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) are two frameworks which operationalize depth of processing of a vocabulary learning task. However, there is dearth of research comparing the predictive power of the ILH and the TFA across second language (L2) vocabulary learning tasks. The present study, therefore, aimed to examine this issue across four vocabulary learning...

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...