Abstract: A display device and method for manufacturing thereof are provided. The display device includes a substrate having a display area and a non-display area, and including an edge, an upper surface having an edge area in which a processing trace remains adjacent to the edge, a bottom surface opposite to the upper surface, a side surface connected to the upper surface and not parallel thereto, and a first inclined surface connected to the side surface and to the bottom surface, a light-emitting element layer above the upper surface of the substrate in the display area, and including light-emitting elements, an encapsulating layer above the light-emitting element layer and corresponding to a portion of the display area and the non-display area, and a protective layer above an outer surface of the substrate, and located on at least one of the bottom surface, the side surface, or the first inclined surface.

Abstract: A display device includes: a substrate including a display area and a non-display area surrounding the display area; a light emitting element layer on the display area on the substrate and including a plurality of light emitting elements; and an encapsulating layer on the light emitting element layer and on a portion of the display area and the non-display area; and wherein the substrate comprises an upper surface on which the light emitting element layer is located, a bottom surface opposite to the upper surface, a side surface connected to the upper surface and not parallel to the upper surface, and a first inclined surface connected to the side surface and the bottom surface and not parallel to the side surface and the bottom surface, wherein an edge area of the upper surface of the substrate adjacent to an edge of the substrate, in which a processing trace remains.

Abstract: A display device includes: a substrate comprising an upper surface, a bottom surface facing the upper surface, and a through hole penetrating the upper surface and the bottom surface; and a light emitting element layer on the upper surface of the substrate, wherein the substrate comprises a side surface that meets the upper surface in the through hole, a first surface that meets the bottom surface, a second surface that meets the side surface, and a third surface between the first surface and the second surface, and wherein the first surface and the second surface are spaced apart from each other with the third surface therebetween, and are inclined surfaces.

Abstract: An electronic device includes a display device, which may be fabricated using a described method. The display device includes a glass substrate including a first surface, a second surface opposite the first surface, and a side surface between the first surface and the second surface, an outermost structure on the first surface of the glass substrate and located adjacent to an edge of one side of the glass substrate, and a display area including a plurality of light emitting areas on the first surface of the glass substrate and located farther from the edge of the one side of the glass substrate than the outermost structure is. A minimum distance from the side surface of the glass substrate to the outermost structure is equal to 130 ?m or less.

Abstract: A method for predicting a clamp force using a convolutional neural network includes: generating a cepstrum image from a signal processing analysis apparatus; extracting a characteristic image by multiplying a predetermined weight value to pixels of the generated cepstrum image through artificial intelligence learning; extracting, as a representative image, the largest pixel from the extracted characteristic image; synthesizing an image by synthesizing the extracted representative image information; and predicting a clamp force by comparing the synthesized image with a predetermined value.

Abstract: An axial force measurement apparatus measuring an axial force of a bolt member by measuring a clamping force, of a nut member threaded onto the bolt member, which is applied to fasten a structure, includes: a sensor that applies vibration to the structure through one side of the tightened nut member and obtains, on an opposite side of the nut member, a signal by the vibration that propagates through the structure and passes through the nut member; and an analyzer that analyzes the signal received from the sensor and determines the axial force of the bolt member using a difference in propagation velocity of the signal by the vibration according to the clamping force of the nut member.

Abstract: An axial force measurement apparatus measuring an axial force of a bolt member by measuring a clamping force, of a nut member threaded onto the bolt member, which is applied to fasten a structure, includes: a sensor that applies vibration to the structure through one side of the tightened nut member and obtains, on an opposite side of the nut member, a signal by the vibration that propagates through the structure and passes through the nut member; and an analyzer that analyzes the signal received from the sensor and determines the axial force of the bolt member using a difference in propagation velocity of the signal by the vibration according to the clamping force of the nut member.

Abstract: A method of estimating clamp force of a bolt may include converting and analyzing, by a signal processing and analyzing device, a learning signal for the clamp force of the bolt, the learning signal being acquired by a data acquirement device; comparing the learning signal classified into groups according to signal characteristics by the converting and analyzing, with a discriminant signal desired to be estimated; and estimating, as clamp force of the discriminant signal, clamp force corresponding to a signal of a most similar group among the learning signal classified into the groups by the comparing.

Abstract: A method for predicting a clamp force using a convolutional neutral network method includes: generating a cepstrum image from a signal processing analysis apparatus; extracting a characteristic image by multiplying a predetermined weight value to pixels of the generated cepstrum image through artificial intelligence learning; extracting, as a representative image, the largest pixel from the extracted characteristic image; synthesizing an image by synthesizing the extracted representative image information; and predicting a clamp force by comparing the synthesized image with a predetermined value.