Abstract: An ammunition monitoring apparatus of the present disclosure includes at least one object-position detection sensor and a controller. The at least one object-position detection sensor is installed near a shell or charge route to face at least one set area and to output position information of each shell or charge in the at least one set area. The controller is configured to determine whether a position range occupied by the shell or the charge in the at least one set area exceeds an allowable position range, based on the position information received from the at least one object-position detection sensor, and to output an alert signal indicating a poor position upon determining that the position range occupied by the shell or the charge in the at least one set area exceeds the allowable position range.

Abstract: An ammunition monitoring apparatus of the present disclosure includes at least one object-position detection sensor and a controller. The at least one object-position detection sensor is installed near a shell or charge route to face at least one set area and to output position information of each shell or charge in the at least one set area. The controller is configured to determine whether a position range occupied by the shell or the charge in the at least one set area exceeds an allowable position range, based on the position information received from the at least one object-position detection sensor, and to output an alert signal indicating a poor position upon determining that the position range occupied by the shell or the charge in the at least one set area exceeds the allowable position range.

Abstract: There is provided a system for recommending a TV program based on content, the system including: a terminal device configured to: decode and output a received broadcast stream; extract affectors by analyzing a video that is being played by the video player; estimate affects that are an implicit response of a viewer of the video; and learn a preference model using an affect matching each of the affectors and transmit the learned preference model to a recommendation server, and a recommendation server configured to: in response to receipt of a preference model, estimate real-time preference by applying the preference model to each of the plurality of channels in real time; and register a specific TV program in a recommendation list and transmit the recommendation list to the terminal device in a case where a real-time preference for the specific TV program is equal to or greater than a predetermined level.