This paper proposes a parallel machine learning framework for detecting Alzheimer’s disease through T1-weighted MRI scans localised to the hippocampus, segmented between left and right hippocampi. Feature extraction is first performed by 2 separately trained, unsupervised based AutoEncoders, where hippocampi are fed into their respective AutoEncoder. Classification then pair of classifiers on e...

permeability prediction problem has been examined using several methods such as empirical formulas, regression analysis and intelligent systems especially neural networks and fuzzy logic. this study proposes an improved and novel model for predicting permeability from conventional well log data. the methodology is integration of empirical formulas, multiple regression and neuro-fuzzy in a commi...

Parallel corpus is a key component of statistical and Neural Machine Translation (NMT). While most research focuses on machine translation, creation studies are limited for many languages no paper Mizo–English exists yet. A high-quality parallel required Natural Language Processing (NLP) activities including Chatbots, Transliteration, Cross-Language Information Retrieval. This work aims to inve...

Unchained from the confines of controller limitations, the industrial application of parallel kinematic machines in manufacturing is beginning to emerge. The launch of commercially available hexapod machine tools at the 1994 International Manufacturing Technology Show in Chicago represented the first radical departure in machine tool design since the introduction of numerical controls. The para...