Abstract: An apparatus of tilting a seat cushion of a vehicle, includes a tilting motor, a pinion gear, a sector gear, and a tilting link which perform the tilting operation of the seat cushion and exert a binding force in a tilted state of the seat cushion and are provided to be connected to both of one side and the other side of a seat cushion frame, and has two sector gears positioned on left and right sides and connected to each other by a connection bar so that, by strengthening a binding force of the front portion of the seat cushion, it is possible to secure the safety of passengers in the event of a collision.

Abstract: A human-following robot for searching a following target when failing to track the following target includes a location estimating module configured to estimate a location of the following target based on map information and trajectory information, a search range setting module configured to set a search range of the following target based on the estimated location information and human walking pattern information, and tracking module configured to track the following target after moving to the search range. Since the robot estimates a location of a missed following target and the moves to the estimated location by utilizing map information and human walking pattern information including walking pattern data of persons in a surrounding environment, which is accumulated during a predetermined period, the following target may be detected again.

Abstract: A human-following robot for searching a following target when failing to track the following target includes a location estimating module configured to estimate a location of the following target based on map information and trajectory information, a search range setting module configured to set a search range of the following target based on the estimated location information and human walking pattern information, and tracking module configured to track the following target after moving to the search range. Since the robot estimates a location of a missed following target and the moves to the estimated location by utilizing map information and human walking pattern information including walking pattern data of persons in a surrounding environment, which is accumulated during a predetermined period, the following target may be detected again.

Abstract: The present disclosure relates to an apparatus and method supportive of distributed turbo coding based on relay network utilizing a noisy network coding scheme. For this, included is a relay node operating as a component encoder to relay a signal from a source node to a next node in a distributed turbo coding scheme. The relay node quantizes the signal transmitted from the source node and then interleaves the quantized signal using a predetermined pattern to distinguish the signal transmitted from the source node from a signal to be output from an opposing node, so that the signal transmitted from the source node is relayed to the next node based on a noisy network coding scheme.

Abstract: The present disclosure relates to an apparatus and method supportive of distributed turbo coding based on relay network utilizing a noisy network coding scheme. For this, included is a relay node operating as a component encoder to relay a signal from a source node to a next node in a distributed turbo coding scheme. The relay node quantizes the signal transmitted from the source node and then interleaves the quantized signal using a predetermined pattern to distinguish the signal transmitted from the source node from a signal to be output from an opposing node, so that the signal transmitted from the source node is relayed to the next node based on a noisy network coding scheme.

Abstract: Disclosed is an apparatus for training a recognition capability by using a robot and to a method for same. Disclosed is the apparatus for training the recognition capability, according to one embodiment of the present invention, comprising: an instruction generation portion for transmitting to the robot a series of robot instructions for controlling the behavior of the robot; a sensor portion for collecting sensor information including a 3D position information and color information of a trainee; a trainee behavioral information generation portion for generating behavioral information of the trainee, based on the sensor information that is collected; and a recognition capability determination portion for outputting the recognition capability of the trainee, based on the robot instructions and the behavioral information of the trainee.