Methods to solve natural gas loadflow problems using electric loadflow techniques are presented. The motivation is to integrate a natural gas network with an electric power transmission network so that the network analysis for a combined natural gas and electric power distribution network can be performed in a consistent manner. The issues arising from solving gas loadflow problems are discusse...

The proliferation of deep learning methods in natural language processing (NLP) and the large amounts of data they often require stands in stark contrast to the relatively data-poor clinical NLP domain. In particular, large text corpora are necessary to build high-quality word embeddings, yet often large corpora that are suitably representative of the target clinical data are unavailable. This ...

Drug-drug interaction (DDI) is a vital information when physicians and pharmacists intend to co-administer two or more drugs. Thus, several DDI databases are constructed to avoid mistakenly combined use. In recent years, automatically extracting DDIs from biomedical text has drawn researchers’ attention. However, the existing work utilize either complex feature engineering or NLP tools, both of...

Neural network techniques are widely applied to obtain high-quality distributed representations of words, i.e., word embeddings, to address text mining and natural language processing tasks. Recently, efficient methods have been proposed to learn word embeddings from context that captures both semantic and syntactic relationships between words. However, it is challenging to handle unseen words ...

The article describes information network and CATV applications, backbone network structure. Cable is a natural network for carrying high-capacity, bandwidth intense information. In the age of analogue program signals, cable’s capacity was a natural transmission media for broadcast colour TV and high-fidelity stereo sound programs. In the new digital program signal age, cable’s high capacity is...

Abstract Full scale simulations of neuronal network models the brain are challenging due to high density connections between neurons. This contribution reports run times shorter than simulated span biological time for a full model local cortical microcircuit with explicit representation synapses on recent conventional compute node. Realtime performance is relevant robotics and closed-loop appli...