Abstract: Provided is a computing system having a hierarchical memory structure. When a data structure is allocated with respect to a task processed in the computing system, the data structure is divided and a portion of the data structure is allocated to a high speed memory of the hierarchical memory structure and a remaining data structure is allocated to a low speed memory of the hierarchical memory.

Abstract: Disclosed herein are a speed limit sign recognition system and method using a front camera which can track a traffic sign continuously appearing in images which are obtained by a photographing speed limit sign located in front of a driver using a camera mounted on the front of the vehicle, recognize an internal numeral of the traffic sign, and inform the driver of an actual limit speed through the recognized numeral, including: an image acquisition unit for acquiring a front image using a front camera; a traffic sign detector for detecting a traffic sign from the acquired front image; a recognition unit for recognizing an internal numeral in the detected traffic sign; a tracking unit for tracking a traffic sign continuously appearing in the front image, and eliminating a temporarily misrecognized object; and a decision unit for determining a result of speed limit recognition on the recognized traffic sign.

Abstract: Disclosed herein are a speed limit sign recognition system and method using a front camera which can track a traffic sign continuously appearing in images which are obtained by a photographing speed limit sign located in front of a driver using a camera mounted on the front of the vehicle, recognize an internal numeral of the traffic sign, and inform the driver of an actual limit speed through the recognized numeral, including: an image acquisition unit for acquiring a front image using a front camera; a traffic sign detector for detecting a traffic sign from the acquired front image; a recognition unit for recognizing an internal numeral in the detected traffic sign; a tracking unit for tracking a traffic sign continuously appearing in the front image, and eliminating a temporarily misrecognized object; and a decision unit for determining a result of speed limit recognition on the recognized traffic sign.

Abstract: Disclosed herein is a method of sensor network localization through reconstruction of a radiation pattern with a characteristic value of an antenna depending on orientation thereof. The method can minimize errors using an antenna characteristic value and a signal strength depending on the orientation. In addition, the method can minimize errors using an artificial neural network to characterize a distorted radiation pattern of an antenna and using it for the localization of a triangulation method. Furthermore, the method can increases the localization rate even in a passive localization method by characterizing an asymmetric antenna radiation pattern and constructing the antenna characteristic through an artificial neural network.

Abstract: Provided is a computing system having a hierarchical memory structure. When a data structure is allocated with respect to a task processed in the computing system, the data structure is divided and a portion of the data structure is allocated to a high speed memory of the hierarchical memory structure and a remaining data structure is allocated to a low speed memory of the hierarchical memory.

Abstract: The present invention relates to III-nitride semiconductor light emitting device and a method for fabricating the same. The III-nitride semiconductor light emitting device includes: a substrate; a plurality of III-nitride semiconductor layers grown over the substrate and including an active layer for generating light by recombination of electrons and holes; and a protrusion formed on a surface of the substrate over which the semiconductor layers are to be grown, a section of the protrusion which is in parallel to the growth direction of the semiconductor layers being formed in a triangular shape.

Abstract: The present disclosure relates to a III-nitride semiconductor light emitting device, including: a substrate; a plurality of III-nitride semiconductor layers grown over the substrate and including an active layer generating light by recombination of electrons and holes; a scattering surface provided on the substrate to scatter the light generated in the active layer; and a sub-scattering portion ruggedly formed on the scattering surface.

Abstract: Disclosed herein is a method of sensor network localization through reconstruction of a radiation pattern with a characteristic value of an antenna depending on orientation thereof. The method can minimize errors using an antenna characteristic value and a signal strength depending on the orientation. In addition, the method can minimize errors using an artificial neural network to characterize a distorted radiation pattern of an antenna and using it for the localization of a triangulation method. Furthermore, the method can increases the localization rate even in a passive localization method by characterizing an asymmetric antenna radiation pattern and constructing the antenna characteristic through an artificial neural network.