Over the last 20 years Machine Learning (ML) has been applied to a wide variety of
applications in the fields of engineering and computer science. In the field of material …

Manufacturing of fiber reinforced polymer matrix composite materials is being done with
various methods in recent days. But controlling the accuracy of manufacturing and begetting …

Discovery of new materials is increased after the introduction of high accuracy machine
learning techniques in the field of material science. Traditional way of discovering new …

Generally, dynamic model selection is implemented using algorithms that need a feedback
from the system's output; but, in many real-world applications this feedback is not available …

This paper presents a novel deep learning architecture named multi-scale neighborhood
query graph convolutional network (MNQGN). In MNQGN, the spatial relationship between …

Explicit knowledge can often be shared through textbooks, technical papers, instruction
manuals, guides, and videos. It is normally objective, logical and technical. However, tacit …

The accurate prediction of failure of load-bearing fiber-reinforced structures remains a
challenge due to the complex interacting failure modes at multiple length scales. In recent …

Featured Application The application of “Autonomous Navigation of Robots: Optimization
with DQN” involves using reinforcement learning techniques to optimize the navigation of …

Given the greater global awareness of environmental impacts of plastics and the need to
develop alternative materials from renewable natural resources, there has been an …

Fiber composites must be evaluated to achieve correct use in various fields. Their
properties, performance, condition, and integrity can be quickly predicted and optimized by …