Abstract: Computer-readable media, methods, and systems are disclosed for converting a diagram into a digital diagram format. A diagram is received as an image file and a plurality of recognition stages produce a final diagram based on predicted information from one or more of the recognition stages. The plurality of recognition stages including a shape detection stage for detecting a plurality of shapes and at least one arrow detection stage in which arrows are detected as relations between pairs of shapes. The final diagram is generated based on the predicted information and is converted into the digital diagram format compatible with a diagram modeling language.

Abstract: Computer-readable media, methods, and systems are disclosed for converting a diagram into a digital diagram format. A diagram is received as an image file and a plurality of recognition stages produce a final diagram based on predicted information from one or more of the recognition stages. The plurality of recognition stages including a shape detection stage for detecting a plurality of shapes and at least one arrow detection stage in which arrows are detected as relations between pairs of shapes. The final diagram is generated based on the predicted information and is converted into the digital diagram format compatible with a diagram modeling language.

Abstract: Systems, methods, and computer programmable products are described herein for generating a robotic process automation bot script from a handwritten sketch. A digitally encoded image having a handwritten diagram with objects is received. The handwritten diagram is converted into a digital flowchart having a plurality of nodes. A confidence score is determined for the nodes based on (i) a textual similarity of contents of the node and a plurality of executable bot activities or (ii) a contextual similarity between a set of activities which measures how often they coappear in a plurality of reference bots. A robotic process automation bot script is generated by mapping the plurality of nodes to an executable bot activity of the plurality of executable bot activities based on the confidence score. The robotic process automation bot is then provided to a robotic process automation system for further modeling.

Abstract: Systems, methods, and computer programmable products are described herein for generating a robotic process automation bot script from a handwritten sketch. A digitally encoded image having a handwritten diagram with objects is received. The handwritten diagram is converted into a digital flowchart having a plurality of nodes. A confidence score is determined for the nodes based on (i) a textual similarity of contents of the node and a plurality of executable bot activities or (ii) a contextual similarity between a set of activities which measures how often they coappear in a plurality of reference bots. A robotic process automation bot script is generated by mapping the plurality of nodes to an executable bot activity of the plurality of executable bot activities based on the confidence score. The robotic process automation bot is then provided to a robotic process automation system for further modeling.

Abstract: Systems, methods, and devices are described herein for handwritten diagram recognition using machine learning. A machine learning component receives a digitally encoded image having a handwritten diagram. The machine learning component localizes and classifies a plurality of objects within the handwritten diagram. A structure recognition component identifies connections between each symbol of the plurality of objects based on content of the respective object. A handwriting recognition component interprets one or more alphanumeric text strings within a portion of the plurality of objects. A digital structured model of the digitally encoded image is automatically generated, without human intervention. The digital structured model has the identified connections among the plurality of objects and is in a computer-readable editable format.

Abstract: Systems, methods, and devices are described herein for handwritten diagram recognition using machine learning. A machine learning component receives a digitally encoded image having a handwritten diagram. The machine learning component localizes and classifies a plurality of objects within the handwritten diagram. A structure recognition component identifies connections between each symbol of the plurality of objects based on content of the respective object. A handwriting recognition component interprets one or more alphanumeric text strings within a portion of the plurality of objects. A digital structured model of the digitally encoded image is automatically generated, without human intervention. The digital structured model has the identified connections among the plurality of objects and is in a computer-readable editable format.

Abstract: The invention relates to a method for regulating the minimal value of the pressure in the first half of the metering zone in a direction of conveyance in a single-screw degassing extruder or in a cascade extruder during the conveying of a melt consisting of a thermoplastic. The single-screw degassing extruder or the cascade extruder each have a first screw section (13), a degassing zone (14), a metering zone (22), and a measuring control loop (M), which includes a pressure measuring sensor (P) in the first half of the metering zone, a regulator (R) and an actuator (S) for influencing the pressure in the metering zone. The pressure is measured by the pressure measuring sensor (P) and is set by the regulator (R) and the actuator (S) so that the minimal value at the location of measurement ranges from 0.1 to 10 bar.

Abstract: The invention relates to a method for regulating the minimal value of the pressure in the first half of the metering zone in a direction of conveyance in a single-screw degassing extruder or in a cascade extruder during the conveying of a melt consisting of a thermoplastic. The single-screw degassing extruder or the cascade extruder each have a first screw section (13), a degassing zone (14), a metering zone (22), and a measuring control loop (M), which includes a pressure measuring sensor (P) in the first half of the metering zone, a regulator (R) and an actuator (S) for influencing the pressure in the metering zone. The pressure is measured by the pressure measuring sensor (P) and is set by the regulator (R) and the actuator (S) so that the minimal value at the location of measurement ranges from 0.1 to 10 bar.

Abstract: A plastic body including a base molded body produced from a transparent, thermoplastic base material, and that includes at least two opposing flat layers interconnected by vertical or diagonal connecting elements. One of the flat layers is provided with an additional layer of a plastic matrix in a transparent, plastic base material. The additional layer is an IR-absorbent layer containing at least one IR-absorber that does not impair transparency of the plastic body and has an average transmission of less than 80% in the region of the near-infrared radiation (780 nm to 1100 nm). The plastic body has a light transmission of between 15% and 86%, a maximum heat transition coefficient of 4 W/m2K and a minimum Sk value of 1.15. The plastic body can be used, e.g., as a glazing element, a roofing element, a heat insulating element.

Abstract: A film comprising at least one layer of fluorine polymers and poly(meth)acrylates is prepared by (i) preparing a mixture of fluorine polymer and poly(meth)acrylate; and (ii) extruding the mixture maintained below its gel-forming temperature through the die of an extruder having a filter placed before entry of the mixture into the die, the temperature of the die being maintained higher than the temperature of the composition upon entry into the die but lower than the gel-forming temperature of the mixture, onto a roll having a temperature ≦100° C., thereby forming the at least one layer in the shape of a film.