Abstract:
Example implementations described herein are directed to the management of data received from an edge side when an update is issued to edge nodes from a core apparatus. When the edge nodes receive the update, the receipt of the update may not be uniform (e.g., due to latency, downtime, etc.), which results in an intermediate state where some edge nodes are updated and some edge nodes are not. Example implementations described herein address the processing of data from edge nodes when such an intermediate state occurs by conducting reprocessing of data when data is transmitted from edge nodes operating from an old configuration.
Abstract:
A database management system determines whether an exhibition performance, which is a performance exhibited by execution of a query being in execution, satisfies a predetermined condition continuously on and after a certain time point, based on an execution state of the database management system. When the determination result is affirmative and there is an execution-waiting query, the database management system starts execution of the execution-waiting query before execution of the query being in execution ends.
Abstract:
Example implementations described herein involve integrating human observations into results of a machine learning process to generate an integrated failure prediction and updated machine learning models from human observations. Example implementations can involve systems and methods that, for receipt of a user input indicative of a failure symptom at a facility, conducting cause estimation on the failure symptom to determine a first set of probabilities associated with a first set of causes of the failure symptom; and integrating the first set of probabilities and first set of causes into a process configured to provide a second set of probabilities and a second set of causes of the failure symptom based on a set of potential failures associated with a third set of probabilities provided from a machine learning process configured to output the set of potential failures and the third set of probabilities based on sensor data from the facility.
Abstract:
Example implementations described herein involve defect analysis for images received from a camera system, which can involve applying a first model configured to determine regions of interest of the object from the images, applying a second model configured to identify localized areas of the object based on the regions of interest on the images; and applying a third model configured to identify defects in the localized ones of the images.
Abstract:
A database management system (DBMS) generates a query execution plan including information representing one or more database (DB) operations necessary for executing a query and executes the query based on the query execution plan. In the execution of the query, the DBMS dynamically generates a task for executing a DB operation and executes the dynamically generated task. The DBMS executes a task in a plurality of threads executed by a processor core.
Abstract:
Example implementations are directed to systems and methods that involve obtaining, at a first service robot from a plurality of service robots, data regarding one or more types of services to be executed by one or more second service robots from the plurality of service robots, in response to a human interacting with the first service robot; selecting the one or more second service robots from the plurality of service robots to execute the one or more types of services; and instructing the selected one or more second service robots to execute the one or more types of services.