Abstract: A lighting device includes a plurality of LED light sources, a plurality of lens parts respectively disposed on front surfaces of the plurality of LED light sources to collect and irradiate light emitted from each of the plurality of LED light sources, and a controller for controlling operations of the plurality of LED light sources, wherein the plurality of LED light sources include visible-light LEDs and at least one ultraviolet LED and each of the plurality of lens parts includes a condensing lens disposed on the front surface of each of the plurality of LED light sources to decrease a divergence angle of light emitted from each of the plurality of LED light sources and a fly eye lens part disposed on a front surface of the condensing lens to stack the light on a light receiving surface.

Abstract: Disclosed are an electronic device and method for providing an event management service.

Abstract: The present invention relates to a neural network parameter optimization method and a neural network computation method and apparatus suitable for hardware implementation. The neural network parameter optimization method suitable for hardware implementation according to the present invention may include transforming an existing parameter of a neural network into a signed parameter and a magnitude parameter having a single value for each channel and generating an optimized parameter by pruning the transformed magnitude parameter. Accordingly, the present invention provides a neural network parameter optimization method and a neural network computation method and apparatus thereof, which optimize a large amount of computation and parameters of a convolutional neural network to be effective in hardware implementation, thereby achieving minimal accuracy loss and maximum computation speed.

Abstract: Disclosed are an electronic device and method for providing an event management service.

Abstract: Disclosed herein are novel microorganisms having excellent biodegradability and a method for the bioremediation of oil-contaminated soil. The novel microorganisms are specified as Rhodococcus baikoneurensis EN3 KCTC19082, Acinetobacter johnsonii EN67 KCTC12360 and Acinetobacter haemolyticus EN96 KCTC12361. In the bioremediation method, in addition to said novel microorganisms, various microorganisms of Nocardia sp., Gordonia sp., Rhodococcus sp. and Acinetobactor sp. can be used, and the oil biodegradation activities of these microbial strains can be increased by adding biosurfactant 2-alkyl-3-hydroxylic acid or its derivative. According to the disclosed invention, oil-contaminated soils can be purified in an effective, economical and eco-friendly manner compared to prior bioremediation methods.