41 research outputs found
Variation of some chemical and functional properties of Bambara groundnut (Voandzeia Subterranean L. Thouars) during sort time storage
Stability of chocolate bars fortified with nanocapsules carotenoid of Spirulina platensis
Relationship between rice grain amylose and pasting properties for breeding better quality rice varieties
QTL detection of rice grain quality traits by microsatellite markers using an indica rice (Oryza sativa L.) combination
RHEOLOGY OF RICE-FLOUR PASTES: RELATIONSHIP OF PASTE BREAKDOWN TO RICE QUALITY, AND A SIMPLIFIED BRABENDER VISCOGRAPH TEST
Characterization of indica-type giant embryo mutant rice enriched with nutritional components
Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control
The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC