Abstract: A display device includes: a substrate; a first pixel electrode and a second pixel electrode on the substrate; a dummy pixel electrode between the first pixel electrode and the second pixel electrode, and to receive a dummy voltage; an emissive layer on the first pixel electrode, the second pixel electrode, and the dummy pixel electrode; and a common electrode on the emissive layer. The first pixel electrode is to receive a pixel voltage different from the dummy voltage.

Abstract: A tape measure having a light emitting device includes a housing, a reel received in the housing, and a blade wound on the reel to be extended or retracted through an inlet of the housing, and further includes a first case, a second case coupled with the first case to form the housing, a light emitting portion positioned in front of the center of the reel around the inlet of the housing, and a light emitting circuit portion positioned in the rear side of the center of the reel by facing the light emitting portion, wherein the light emitting circuit portion includes a circuit board disposed on a rear lower side of the housing, and the first case and the second case provide circuit receiving spaces for receiving the circuit board, respectively.

Abstract: Provided is a display device including a display panel including a light emitting element layer and a light control layer on the light emitting element layer, and a color filter panel on the display panel, the color filter panel includes a base layer, a color filter layer below the base layer, a low refractive layer below the color filter layer, and a spacer between the color filter layer and the low refractive layer, and sides of the spacer are covered by the low refractive layer.

Abstract: Provided are a hyperparameter optimizer and method for optimizing hyperparameters and a spiking neural network processing unit. The optimizer includes a statistical analyzer configured to receive training data and perform statistical analysis on the training data, an objective function generator configured to generate hyperparameter-specific objective functions by using a statistical analysis value of the statistical analyzer, and an optimal hyperparameter selector configured to select optimal hyperparameters according to certain rules on the basis of the hyperparameter-specific objective functions.

Abstract: Provided are a hyperparameter optimizer and method for optimizing hyperparameters and a spiking neural network processing unit. The optimizer includes a statistical analyzer configured to receive training data and perform statistical analysis on the training data, an objective function generator configured to generate hyperparameter-specific objective functions by using a statistical analysis value of the statistical analyzer, and an optimal hyperparameter selector configured to select optimal hyperparameters according to certain rules on the basis of the hyperparameter-specific objective functions.