Abstract: A memory device includes a driver that drives a data line connected with an external device, an internal ZQ manager that generates an internal ZQ start signal, a selector that selects one of the internal ZQ start signal and a ZQ start command from the external device, based on a ZQ mode, a ZQ calibration engine that generates a ZQ code by performing ZQ calibration in response to a selection result of the selector, and a ZQ code register that loads the ZQ code onto the driver in response to a ZQ calibration command from the external device.

Abstract: A cleaning system is provided. The cleaning system includes a robot cleaner and a station. The robot cleaner includes a pad fixing part on which a cleaning pad is detachably mounted, a lifter to lift a part of the robot cleaner at which the pad fixing part is positioned, and a pad detacher to detach the cleaning pad mounted on the pad fixing part. The station includes a pad storage box in which a cleaning pad that is to be provided to the robot cleaner is stored, a pad coupling part on which a cleaning pad that is to be coupled to the robot cleaner is rested, and a pad supplier to supply the cleaning pad stored in the pad storage box to the pad coupling part.

Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.

Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.

Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.