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Physical Sciences and Mathematics Commons™
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Missouri University of Science and Technology
Electrical and Computer Engineering Faculty Research & Creative Works
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- Big data (1)
- Bigdata (1)
- Capillarity (1)
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- Error-driven learning (1)
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Capillary-Tube Package Devices For The Quantitative Performance Evaluation Of Nuclear Magnetic Resonance Spectrometers And Pulse Sequences, Lingyu Chi, Ming Huang, Annalise R. Pfaff, Jie Huang, Rex E. Gerald Ii, Klaus Woelk
Capillary-Tube Package Devices For The Quantitative Performance Evaluation Of Nuclear Magnetic Resonance Spectrometers And Pulse Sequences, Lingyu Chi, Ming Huang, Annalise R. Pfaff, Jie Huang, Rex E. Gerald Ii, Klaus Woelk
Electrical and Computer Engineering Faculty Research & Creative Works
With the increased sensitivity of modern nuclear magnetic resonance (NMR) spectrometers, the minimum amount needed for chemical-shift referencing of NMR spectra has decreased to a point where a few microliters can be sufficient to observe a reference signal. The reduction in the amount of required reference material is the basis for the NMR Capillary-tube Package (CapPack) platform that utilizes capillary tubes with inner diameters smaller than 150 µm as NMR-tube inserts for external reference standards. It is shown how commercially available electrophoresis capillary tubes with outer diameters of 360 µm are filled with reference liquids or solutions and then permanently …
Nmr Studies Of Loaded Microspheres, Ming Huang, Sisi Chen, Rex E. Gerald Ii, Jie Huang, Klaus Woelk
Nmr Studies Of Loaded Microspheres, Ming Huang, Sisi Chen, Rex E. Gerald Ii, Jie Huang, Klaus Woelk
Electrical and Computer Engineering Faculty Research & Creative Works
Porous-wall hollow glass microspheres (PWHGMs) are a novel form of glass materials that consist of 1-μm-thick porous silica shells, 20-100 μm in diameter, with a hollow cavity in the center. Utilizing the central cavity for material storage and the porous walls for controlled release is a unique combination that renders PWHGMs a superior vehicle for targeted drug delivery. In this study, NMR spectroscopy was used to characterize PWHGMs for the first time. A vacuum-based loading system was developed to load PWHGMs with various compounds followed by a washing procedure that uses solvents immiscible with the target material. Immiscible binary model …
Direct Error Driven Learning For Deep Neural Networks With Applications To Bigdata, R. Krishnan, Jagannathan Sarangapani, V. A. Samaranayake
Direct Error Driven Learning For Deep Neural Networks With Applications To Bigdata, R. Krishnan, Jagannathan Sarangapani, V. A. Samaranayake
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It …