Abstract: A method of forming a pattern of a semiconductor device, the method comprising forming an insulating film on a substrate having a first region and a second region, sequentially forming a lower mask layer and an upper mask layer on the insulating film, forming a line-shaped hard mask pattern having a plurality of narrow openings having the same width in the first region and the second region, respectively, on the upper mask layer, forming line-shaped spacers on sidewalls of the opening of the line-shaped hard mask pattern, forming a composite mask pattern composed of the spacer and a pattern having a first width among the line-shaped hard mask pattern by removing a pattern having a second width among the line-shaped hard mask patterns, the second width being smaller than the first width.

Abstract: An optimization calculation apparatus may comprise an algorithm module obtaining a plurality of first solutions (S1) from a plurality of input data, obtaining second solutions (S2) from the first solutions (S1), and repeating the process to derive an optimal solution (Sm). The optimization calculation apparatus may further comprise a similarity determination module connected to the algorithm module and computing a similarity of ith solutions in order to obtain (i+1)th solutions (1?i?m?1).

Abstract: Disclosed herein are a computing apparatus and method for performing reinforcement learning using a multimodal artificial intelligence agent. The method for performing reinforcement learning using a multimodal artificial intelligence agent includes: dividing frames, included in images acquired by capturing a virtual environment, into a plurality of sections; and performing reinforcement learning by applying any one of a plurality of guidance types to each of the plurality of sections and then allowing a multimodal artificial intelligence agent to interact with the virtual environment through the images. The plurality of guidance types is classified into three or more types according to their guidance level. Performing the reinforcement learning is performing reinforcement learning by applying a moderate-level guidance type to the sections of predetermined critical periods and also applying any one of the plurality of guidance types to the other sections.

Abstract: A toddler-inspired Bayesian learning method according to an embodiment includes: collecting information related to at least one task while an agent is performing exploration; and performing Bayesian inference regarding the at least one task by using the collected information as Bayesian informative priors.

Abstract: A wireless transmitting and receiving device includes antennas, weight adjusters connected to antennas, respectively, and configured to apply weights to an amplitude and a phase of a signal communicating through the antennas, signal transmitting and detecting units connected to the weight adjusters, respectively, a transmitter and a receiver connected to a first switch, a power distributor configured to connect the first switch to the respective signal transmitting and detecting units through internal wirings, and a compensator configured to the weights of the weight adjusters according to output signals of the signal transmitting and detecting units.

Abstract: A wireless transmitting and receiving device includes antennas, weight adjusters connected to antennas, respectively, and configured to apply weights to an amplitude and a phase of a signal communicating through the antennas, signal transmitting and detecting units connected to the weight adjusters, respectively, a transmitter and a receiver connected to a first switch, a power distributor configured to connect the first switch to the respective signal transmitting and detecting units through internal wirings, and a compensator configured to the weights of the weight adjusters according to output signals of the signal transmitting and detecting units.