Abstract: According to one or more embodiments of the present invention, a computer-implemented method for adjusting a process variable using a closed loop system includes initializing a radial basis function neural network (RBF network) using a maximum error (emax), a maximum first order change in error (?emax), a maximum second order change in error (?2emax), and a maximum output increment (?omax), associated with the closed loop system being controlled. The method further includes inputting, to the RBF network, input values including an error, a first order change in error, and a second order change in error. The method further includes computing, by the RBF network, control parameters based on the input values, and computing, by the RBF network, an incremental change in the process variable based on the control parameters. The method further includes adjusting, by a controller, an output device to change the process variable by the incremental change.

Abstract: An enhanced prediction model utilizing product life cycle segmentation and historic prediction data for generating more accurate future failure rates. Input data is segmented into groups based on failure modes of a corresponding life cycle. A prediction model such as Weibull analysis is implemented for each segmented group. Historical prediction data is also segmented into groups. Prediction parameters for each group of segmented historical prediction data are compared with one another and the comparisons are then used to adjust the prediction parameters generated from the segmented groups of input data. Updated parameters for the input data are then output thereby generating a new future failure rate.

Abstract: A method, computer program product, and a system where a processor(s) obtains data comprising trends recognized by an observer of the system over time; data comprised of more than one vintage. The processor(s) transforms the data measurable dimensions and assigns the transformed data to vintages and to distinct periods of time. The processor(s) generates an image from the transformed data that represents the trends, organized by the distinct periods of times and the vintages.

Abstract: A method, computer program product, and a system where a processor(s) obtains data comprising trends recognized by an observer of the system over time; data comprised of more than one vintage. The processor(s) transforms the data measurable dimensions and assigns the transformed data to vintages and to distinct periods of time. The processor(s) generates an image from the transformed data that represents the trends, organized by the distinct periods of times and the vintages.

Abstract: An enhanced prediction model utilizing product life cycle segmentation and historic prediction data for generating more accurate future failure rates. Input data is segmented into groups based on failure modes of a corresponding life cycle. A prediction model such as Weibull analysis is implemented for each segmented group. Historical prediction data is also segmented into groups. Prediction parameters for each group of segmented historical prediction data are compared with one another and the comparisons are then used to adjust the prediction parameters generated from the segmented groups of input data. Updated parameters for the input data are then output thereby generating a new future failure rate.

Abstract: According to one or more embodiments of the present invention, a computer-implemented method for adjusting a process variable using a closed loop system includes initializing a radial basis function neural network (RBF network) using a maximum error (emax), a maximum first order change in error (?emax), a maximum second order change in error (?2emax), and a maximum output increment (?omax), associated with the closed loop system being controlled. The method further includes inputting, to the RBF network, input values including an error, a first order change in error, and a second order change in error. The method further includes computing, by the RBF network, control parameters based on the input values, and computing, by the RBF network, an incremental change in the process variable based on the control parameters. The method further includes adjusting, by a controller, an output device to change the process variable by the incremental change.

Abstract: A case that stores one or more paintbrushes in manner to prevent paint in them from drying out, so that there is no need to clean those brushes between uses; moreover the case containing a pump evacuator to remove air from the case when it is closed, thus further retarding the drying of the brushes inside; and finally the case holding paint drying retardant that evanesces into the atmosphere inside the case, further slowing down the drying of the brushes inside.

Abstract: The present invention relates to a system that includes a package and a plurality of diapers that are within the package. The system further includes an appliqué that is within the package. The appliqué is adapted to be detachably adhered to each of the plurality of diapers in the system. The appliqué may initially be placed on one of the diapers and when the original diaper is discarded, the appliqué may then be transferred to another newly worn diaper in order to promote interaction between a child and the diapers that are used during multiple diaper changes. In some embodiments, the appliqué includes a first graphic and at least one of the diapers in the system includes a second graphic. The first graphic and the second graphic may form a third graphic when the appliqué is detachably adhered to an appropriate location on the diapers that include the second graphic.

Abstract: An absorbent structure made at least in part from a superabsorbent material having a retention capacity (CRC) as determined by a Centrifuge Retention Capacity Test of at least about 25 g/g and a free swell gel bed permeability (GBP) as determined by a Free Swell Gel Bed Permeability Test of at least 575×10?9 cm2. In another embodiment, the absorbent structure is made at least in part from a superabsorbent material having a retention capacity (CRC) as determined by a Centrifuge Retention Capacity Test of at least about 25 g/g, an absorbency under load (AUL) at 0.9 psi as determined by an Absorbency Under Load Test of at least 18 and a free swell gel bed permeability (GBP) as determined by a Free Swell Gel Bed Permeability Test of at least about 350×10?9 cm2.

Abstract: A continuous bulk polymerization and esterification process includes continuously charging into a reaction zone at least one ethylenically unsaturated acid-functional monomer and at least one linear or branched chain alkanol having greater than 11 carbon atoms. The process includes maintaining a flow rate through the reaction zone sufficient to provide an average residence time of less than 60 minutes and maintaining a temperature in the reaction zone sufficient to produce a polymeric product incorporating at least some of the alkanol as an ester of the polymerized ethylenically unsaturated acid-functional monomer. The polymeric product is used in various processes to produce water-based compositions including emulsions and dispersions such as oil emulsions, wax dispersions, pigment dispersions, surfactants and coatings which contain the polymeric product.