Abstract: An industrialized system and method for rice grain recognition. An optical image is taken and transmitted to a digital platform, wherein the system segments the optical image and extracts and/or measures appropriate grain features from the image describing different aspects of the grain. The image is processed by the system which includes a selector selecting different machine learning structures, applying the different machine learning structures to the extracted features for rice grain recognition, and selecting the best of the applied machine learning structures by a random sampling process. The selected best of the applied machine learning structures is further optimized by varying an appropriate threshold by a threshold trigger based on a confusion matrix comprising. An active learning structure based on the confusion matrix to the user. The system is retrained based on the feedback parameters of the feedback loop.

Abstract: A product processing installation and corresponding method for the grinding and/or crushing of granular fruits or the like. There is a self-adaptive regulation and control method and corresponding regulation and control device for the self-optimised control of a mill installation and a grinding line of a roller system of the mill installation. The grinding line include a plurality of processing units, which, based on operational process parameters, can each individually be controlled and individually regulated in their operation by means of the regulation and control device. A batch control with a defined processing sequence in the processing units can be regulated by an operational process recipe, wherein a defined amount of a final product can be produced from one or more input materials by means of the operational process recipe. The processing units are controlled based on specific operational batch process parameters assigned to the operational process recipe.

Abstract: An industrialized system and method for rice grain recognition. An optical image is taken and transmitted to a digital platform, wherein the system segments the optical image and extracts and/or measures appropriate grain features from the image describing different aspects of the grain. The image is processed by the system which includes a selector selecting different machine learning structures, applying the different machine learning structures to the extracted features for rice grain recognition, and selecting the best of the applied machine learning structures by a random sampling process. The selected best of the applied machine learning structures is further optimized by varying an appropriate threshold by a threshold trigger based on a confusion matrix comprising. An active learning structure based on the confusion matrix to the user. The system is retrained based on the feedback parameters of the feedback loop.

Abstract: A product processing installation and corresponding method for the grinding and/or crushing of granular fruits or the like. There is a self-adaptive regulation and control method and corresponding regulation and control device for the self-optimised control of a mill installation and a grinding line of a roller system of the mill installation. The grinding line include a plurality of processing units, which, based on operational process parameters, can each individually be controlled and individually regulated in their operation by means of the regulation and control device. A batch control with a defined processing sequence in the processing units can be regulated by an operational process recipe, wherein a defined amount of a final product can be produced from one or more input materials by means of the operational process recipe. The processing units are controlled based on specific operational batch process parameters assigned to the operational process recipe.

Abstract: Photocurable composition curable by ultraviolet (UV) radiation comprising: A) at least one organosiloxane component A of the following formula (I): whereby Pa and Pb are each independently selected from a cationically polymerizable group, x+y is an integer ?1, Sp and Sp? are each independently selected from a cycloaliphatic hydrocarbon group and an aliphatic linear or branched hydrocarbon group, R1 and R2 are each independently linear or branched aliphatic or cycloaliphatic, alkoxy, aromatic or hetero aromatic groups; B) at least one second organosiloxane component B of the following formula (II): whereby n is an integer ranging from 7 to 300, x+y is an integer ?1, Pa and Pb are each independently selected from a cationically polymerizable group, Sp and Sp? are each independently selected from a cycloaliphatic hydrocarbon group and aliphatic linear or branched hydrocarbon group, R1, R2, R3, R4 are each independently linear or branched aliphatic or cycloaliphatic, alkoxy, aromatic or hetero aromatic group; C)