Gutzwiller
Clément Gutzwiller, Kirchberg CH
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20120240496 | Reinforcing element for built-ins in concrete constructions - Construction elements ( | 09-27-2012 |
Heinz Gutzwiller, Brislach CH
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20080311209 | TOPICAL COMPOSITIONS COMPRISING NANOPARTICLES OF AN ISOFLAVONE - The present invention is directed to topical compositions, comprising isoflavone nanoparticle compositions. The isoflavone nanoparticle compositions contain isoflavone in the form of nanoparticles and preferably a carrier. In the topical compositions recrystallization of the isoflavone to bigger particles is avoided. | 12-18-2008 |
20090035336 | ISOFLAVONE NANOPARTICLES AND USE THEREOF - The present invention is directed to isoflavone nanoparticle compositions comprising isoflavone in the form of nanoparticles and preferably a carrier. The isoflavone nanoparticle compositions are particularly useful for preparing cosmetic compositions, pharmaceutical compositions, foodstuff, food and feed additives. In the compositions comprising the isoflavone nanoparticle compositions recrystallization of the isoflavone to bigger particles is retarded. | 02-05-2009 |
Luke Robert Gutzwiller, Seattle, WA US
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20150254555 | CLASSIFYING DATA WITH DEEP LEARNING NEURAL RECORDS INCREMENTALLY REFINED THROUGH EXPERT INPUT - Embodiments are directed towards classifying data using machine learning that may be incrementally refined based on expert input. Data provided to a deep learning model that may be trained based on a plurality of classifiers and sets of training data and/or testing data. If the number of classification errors exceeds a defined threshold classifiers may be modified based on data corresponding to observed classification errors. A fast learning model may be trained based on the modified classifiers, the data, and the data corresponding to the observed classification errors. And, another confidence value may be generated and associated with the classification of the data by the fast learning model. Report information may be generated based on a comparison result of the confidence value associated with the fast learning model and the confidence value associated with the deep learning model. | 09-10-2015 |
Michael J. Gutzwiller, Cincinnati, OH US
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20100121469 | MULTIFUNCTIONAL VOLLEYBALL SCORE SHEET GENERATOR - Embodiments of the invention provide a method, apparatus, and program product to manage a volleyball match. In some embodiments, the method comprises displaying a set interface operable for a user to record at least one action associated with a volleyball set. The method further includes automatically storing information associated with the at least one action in response to user interaction with the set interface to record the at least one action. Furthermore, the method includes generating a scoresheet that includes the stored information, wherein the scoresheet is based upon a scoresheet template selected from a plurality of scoresheet templates. | 05-13-2010 |
Robert S. Gutzwiller, San Diego, CA US
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20160110551 | Computer System Anomaly Detection Using Human Responses to Ambient Representations of Hidden Computing System and Process Metadata - A system and method involve measuring one or more hidden states internal to a computing system related only to a user's active task with the computing system, using one or more deterministic mapping functions to directly map, without interpretation of the hidden states as being benign or malicious, the measurements to a representational output, presenting the representational output in real-time and peripheral to the user's active task with the computing system without label information pertaining to the hidden states, determining the user's behavioral responses and/or physiological responses to the presented representational output, altering one or more display characteristics of the presented representational output based upon one or more behavioral responses and physiological responses, and/or inputting the user's response into a machine learning algorithm configured to detect an anomaly within the computing system using the user's behavioral and physiological responses and/or computing system measurements. | 04-21-2016 |