Abstract: A sterilization apparatus includes a housing; a sterilization unit for irradiating, with sterilization light, at least one region to be sterilized; and a driving unit for moving the sterilization unit into and out of the housing via an opening of the housing and rotating the sterilization unit about a rotation axis.

Abstract: [SUMMARY] A method of providing an audio mixing interface using multiple audio stems according to embodiment may comprise an audio mixing screen display step which displays an audio mixing screen including an audio block screen indicating audio blocks corresponding to at least one stem item preset for at least one audio version pre-stored for the audio on the display of a user device by the processor, when audio to be mixed is executed by the user, an audio block selection step which displays a selection block on a display of the user device in a shade different from that of the audio blocks by the processor, when the selection block selected by the user exists among the audio blocks displayed on the audio mixing screen and an audio session generation step which combines the audio information included in the selection block and create one session audio, when the user's selection of the audio block is completed.

Abstract: A method for providing information on a user's concept understanding is provided. The method includes acquiring a set of data on a user's understanding of concepts including a first concept estimated using a concept-specific understanding estimation model that is trained on the basis of concept-specific correctness/incorrectness sequence data, estimating the user's understanding of a second concept not encountered by the user using a matrix factorization algorithm on the concept-specific correctness/incorrectness sequence data represented in a matrix structure with respect to the first concept and the second concept, and visualizing the user's understanding of the first concept included in the acquired data set and the second concept on a device of the user. The concept-specific understanding estimation model is trained such that the concept understanding is estimated by assigning a greater weight to a piece of the concept-specific correctness/incorrectness sequence data generated at a later time point.

Abstract: A method for providing a correctness/incorrectness prediction for a learning question is provided. The method includes the steps of: acquiring a set of data including a user variable determined on the basis of concept-specific correctness/incorrectness sequence data of at least one user, and at least one variable related to a question and a concept associated with the user variable; and calculating a probability that a first user corresponding to a specific user variable correctly answers a first question corresponding to a specific concept, with reference to the data set.

Abstract: An illumination apparatus of mobility that implements various illumination functions includes a low beam and a high beam and provides a sense of operation when respective illumination functions are switched such that the design is upgraded.

Abstract: An illumination apparatus of mobility that implements various illumination functions includes a low beam and a high beam and provides a sense of operation when respective illumination functions are switched such that the design is upgraded.

Abstract: Provided are a method for learning task skill and a robot using the same. The modeling method for learning a task skill includes: receiving training data for a task to be performed by a learning engine; dividing, by the learning engine, the received training data into segments by using a geometric property of a predetermined probabilistic model; and learning, by the learning engine, a basis skill for the divided segments by modeling each divided segment.

Abstract: Provided are a method for learning task skill and a robot using the same. The modeling method for learning a task skill includes: receiving training data for a task to be performed by a learning engine; dividing, by the learning engine, the received training data into segments by using a geometric property of a predetermined probabilistic model; and learning, by the learning engine, a basis skill for the divided segments by modeling each divided segment.