Abstract The paper introduces CycleIK, a neuro-robotic approach that wraps two novel neuro-inspired methods for the inverse kinematics (IK) task—a Generative Adversarial Network (GAN), and Multi-Layer Perceptron architecture. These can be used in standalone fashion, but we also show how embedding these into hybrid neuro-genetic IK pipeline allows further optimization via sequential least-square...

Optimization of machining parameters is very important and the main goal in every machining process. Surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. In this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. This approach has both the learning capability of neural network and li...

This paper presents a part of speech (POS) neuro tagger which consists of a 3-layer perceptron with elastic input. Computer experiments show that the neuro tagger has an accuracy of 94.4% for tagging ambiguous words when a small Thai corpus with 22,311 ambiguous words is used for training. A series of comparative experiments further show that the neuro tagger is de nitely far superior to the st...

OBJECTIVE We aimed to investigate the clinical and para clinical manifestations of neuro metabolic disorders, in patients who presented by neuro developmental delay in their neuro developmental milestones. MATERIALS & METHODS The patients diagnosed as neuro developmental delay and regression with or without seizure at the Neurology Department of Mofid Children Hospital in Tehran, Iran between...