Abstract: A moisture exchange fabric is disclosed the fabric comprising: a substrate fabric; a polymer having lower critical solution temperature (LCST) of between 25° C. and 39° C. bonded to the substrate fabric; and a filament sewed into the substrate fabric. Also disclosed is a humidifying apparatus using the moisture exchange fabric.
Abstract: This invention involves use of temporal or spatio/spector-temporal data (SSTD) for early classification of outputs that are results of spatio-temporal patterns of data. Classification models are based on spiking neural networks (SNN) suitable to learn and classify SSTD. The invention may predict early events in many applications, i.e. engineering, bioinformatics, neuroinformatics, predicting response to treatment of neurological and brain disease, ecology, environment, medicine, and economics, among others. The invention involves a method and system for personalized modelling of SSTD and early prediction of events based on evolving spiking neural network reservoir architecture (eSNNr). The system includes a spike-time encoding module to encode continuous value input information into spike trains, a recurrent 3D SNNr and an eSSN as an output classification module.
Type:
Grant
Filed:
August 26, 2014
Date of Patent:
March 3, 2020
Assignee:
AUT Ventures Limited
Inventors:
Nikola Kirilov Kasabov, Zeng-Guang Hou, Valery Feigin, Yixiong Chen