Abstract: A method of pre-warning and identifying a fault of relay protection of an intelligent substation is provided, which is specifically carried out according to following steps. Step 1: performing fault diagnosis on hardware input signals of relay protection equipment; step 2: performing software fault diagnosis on a relay protection device; step 3: developing a MATLAB-based anti-false pre-warning platform for the relay protection of the intelligent substation by combining step 1 and step 2; and step 4: based on the MATLAB-based anti-false pre-warning platform for the relay protection of the intelligent substation, according to fault recording sampling information of the substation, accurately identifying a fault area, pre-judging a possible action situation of protection, and giving pre-warning information.

Abstract: A method of manufacturing a glass assembly to have an opaque boundary feature includes a step of forming a first glass substrate that is curved, with the first glass substrate having an outer surface (P1) and an opposing inner surface (P2), and a second glass substrate that is curved, with the second glass substrate having an inner surface (P3) and an opposing outer surface (P4). The method also includes a step of digitally-applying an organic ink without a mask on at least one of the P2 surface and the P3 surface. The method further includes curing the organic ink to form the opaque boundary feature on at least one of the P2 surface and the P3 surface. The method also further includes disposing a polymeric interlayer between the P2 surface and the P3 surface.

Abstract: A method of manufacturing a glass assembly to have a performance-enhancing feature includes a step of forming a glass substrate that is curved. The method also includes digitally-applying an ink without a mask onto a surface of the curved glass substrate. The method further includes curing the ink to form the performance-enhancing feature on the surface of the curved glass substrate.

Abstract: A 3D shape is reconstructed from a topogram. A generative network is machine trained. The generative network includes a topogram encoder for inputting the topogram and a decoder to output the 3D shape from the output of the encoder. For training, one or more other encoders are included, such as for input of a mask and/or input of a 3D shape as a regularlizer. The topogram encoder and decoder are trained with the other encoder or encoders outputting to the decoder. For application, the topogram encoder and decoder as trained, with or without the encoder for the mask and without the encoder for the 3D shape, are used to estimate the 3D shape for a patient from input of the topogram for that patient.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: A method of manufacturing a glass assembly to have an opaque boundary feature includes a step of forming a first glass substrate that is curved, with the first glass substrate having an outer surface (P1) and an opposing inner surface (P2), and a second glass substrate that is curved, with the second glass substrate having an inner surface (P3) and an opposing outer surface (P4). The method also includes a step of digitally-applying an organic ink without a mask on at least one of the P2 surface and the P3 surface. The method further includes curing the organic ink to form the opaque boundary feature on at least one of the P2 surface and the P3 surface. The method also further includes disposing a polymeric interlayer between the P2 surface and the P3 surface.

Abstract: A method of manufacturing a glass assembly to have a performance-enhancing feature includes a step of forming a glass substrate that is curved. The method also includes digitally-applying an ink without a mask onto a surface of the curved glass substrate. The method further includes curing the ink to form the performance-enhancing feature on the surface of the curved glass substrate.

Abstract: A method of manufacturing a window assembly having a solderless electrical connector includes forming a curved transparent substrate and applying a conductive ink having a thermal degradation temperature onto a surface of the curved transparent substrate. The method further includes applying an adhesive onto the surface of the curved transparent substrate adjacent to the conductive ink and optionally onto the applied conductive ink, and curing the adhesive at a temperature below the thermal degradation temperature of the conductive ink to form the solderless electrical connector with the solderless electrical connector being in electrical contact with the applied conductive ink.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: A method of manufacturing a glass assembly to have a conductive feature includes a step of forming a glass substrate that is curved. The method also includes digitally-applying a conductive ink without a mask onto a surface of the curved glass substrate. The method further includes curing the conductive ink to form the conductive feature on the surface of the curved glass substrate, with the conductive feature having a resolution of greater than 200 dots per inch.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: An unmanned aerial vehicle (UAV) control method includes a takeoff process, a following process and a landing process, wherein the takeoff process includes the following steps: unlocking the UAV, and detecting the current horizontal position of the UAV in the horizontal direction and the current altitude of the UAV in the vertical direction; determining whether the current horizontal position and the current altitude meet takeoff criteria, and controlling the UAV to bounce off and enter into a takeoff state if the determination result is positive. The system provided by the present disclosure employs the above-mentioned method to control a UAV. The method and system provided by the present disclosure meet three functional requirements for a UAV on a moving base platform, namely, stable takeoff, following process and accurate landing, thus decrease the difficulties in the use of a UAV on a moving platform.

Abstract: A treated substrate includes a low emissivity coating layer disposed on a substrate and a high emissivity coating layer disposed on the low emissivity coating layer. The low emissivity coating layer is formed a low emissivity coating composition including silver, or indium tin oxide, or fluorine-doped tin oxide, while the high emissivity coating layer is formed from a high emissivity coating composition including a carbon-doped silicon oxide. The treated substrate has an emissivity of from 0.7 to less than 1.0 at wavelengths ranging from 8 micrometers to 13 micrometers and has an emissivity of greater than 0 to 0.3 at wavelengths less than 6 micrometers. The treated substrate also maintains a visually acceptable mechanical brush durability resistance for at least 150 test cycles tested in accordance with ASTM D2486-17.

Abstract: A 3D shape is reconstructed from a topogram. A generative network is machine trained. The generative network includes a topogram encoder for inputting the topogram and a decoder to output the 3D shape from the output of the encoder. For training, one or more other encoders are included, such as for input of a mask and/or input of a 3D shape as a regularlizer. The topogram encoder and decoder are trained with the other encoder or encoders outputting to the decoder. For application, the topogram encoder and decoder as trained, with or without the encoder for the mask and without the encoder for the 3D shape, are used to estimate the 3D shape for a patient from input of the topogram for that patient.

Abstract: An unmanned aerial vehicle (UAV) control method includes a takeoff process, a following process and a landing process, wherein the takeoff process includes the following steps: unlocking the UAV, and detecting the current horizontal position of the UAV in the horizontal direction and the current altitude of the UAV in the vertical direction; determining whether the current horizontal position and the current altitude meet takeoff criteria, and controlling the UAV to bounce off and enter into a takeoff state if the determination result is positive. The system provided by the present disclosure employs the above-mentioned method to control a UAV. The method and system provided by the present disclosure meet three functional requirements for a UAV on a moving base platform, namely, stable takeoff, following process and accurate landing, thus decrease the difficulties in the use of a UAV on a moving platform.

Abstract: Techniques are provided for making a coated article including an antibacterial and/or antifungal coating. In certain example embodiments, the method includes providing a first sputtering target including Zr; providing a second sputtering target including Zn; and co-sputtering from at least the first and second sputtering targets in the presence of nitrogen to form a layer including ZnxZryNz on a glass substrate. These layers may be heat-treated or thermally tempered to form a single layer including ZnxZryOz. In other examples, two discrete layers of Zn and Zr may be formed. The coating may be heated or tempered to form a single layer including ZnxZryOz. Coated articles made using these methods may have antibacterial and/or antifungal properties.

Abstract: Techniques are provided for making a coated article including an antibacterial and/or antifungal coating. In certain example embodiments, the method includes providing a first sputtering target including Zr; providing a second sputtering target including Zn; and co-sputtering from at least the first and second sputtering targets in the presence of nitrogen to form a layer including ZnxZryNz on a glass substrate. These layers may be heat-treated or thermally tempered to form a single layer including ZnxZryOz. In other examples, two discrete layers of Zn and Zr may be formed. The coating may be heated or tempered to form a single layer including ZnxZryOz. Coated articles made using these methods may have antibacterial and/or antifungal properties.

Abstract: A treated substrate includes a low emissivity coating layer disposed on a substrate and a high emissivity coating layer disposed on the low emissivity coating layer. The low emissivity coating layer is formed a low emissivity coating composition including silver, or indium tin oxide, or fluorine-doped tin oxide, while the high emissivity coating layer is formed from a high emissivity coating composition including a carbon-doped silicon oxide. The treated substrate has an emissivity of from 0.7 to less than 1.0 at wavelengths ranging from 8 micrometers to 13 micrometers and has an emissivity of greater than 0 to 0.3 at wavelengths less than 6 micrometers. The treated substrate also maintains a visually acceptable mechanical brush durability resistance for at least 150 test cycles tested in accordance with ASTM D2486-17.

Abstract: A treated substrate comprise a substrate, an adhesion promoter layer disposed on the substrate, and a topcoat layer disposed on the adhesion layer such that the adhesion layer is between the topcoat layer and the substrate. The adhesion promoter layer is formed from an adhesion promoter composition, with the adhesion promoter composition comprising a polyhedral oligomeric silsesquioxane or a linear organosilane polymer. The topcoat layer is formed from a topcoat composition, with the topcoat composition comprising at least one fluorinated organic silicon compound which contains no etheric oxygen atom and at least one fluorinated organic silicon compound which contains an etheric oxygen atom.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.