Abstract: According to one embodiment, an estimation device acquires a data set from history data. The history data includes a plurality of data IDs, path information, first and second qualitative variables. The data IDs respectively indicate a plurality of data flowing through a plurality of nodes. The path information indicates a path of the nodes for each of the data. The first and second qualitative variables are mutually-independent and indicate classifications of each of the data IDs. The data set includes a part of the data IDs having a first variable value assigned as the first qualitative variable. The estimation device estimates an overall relevance indicating a relevancy to the data set for each of the nodes. The estimation device generates a plurality of partial data sets. The estimation device estimates a partial relevance indicating a relevancy to each of the partial data sets for each of the nodes.

Abstract: According to one embodiment, system includes a determination unit, a first storage, a second storage, a search unit and a display. The determination unit determines a feature quantity of the process-targeted manufacturing data. The first storage stores cause-unidentified manufacturing data. The second storage stores cause-identified manufacturing data. The search unit searches, based on the feature quantity of the process-targeted manufacturing data, the first storage and the second storage for the cause-unidentified manufacturing data and the cause-identified manufacturing data that have a feature quantity similar to that of the process-targeted manufacturing data. The display displays the search result.

Abstract: According to an embodiment, an information processing apparatus includes one or more processors. The processors are configured to: generate a plurality of shuffle maps obtained by randomly shuffling, from positions to others, at least some of subject values contained in a subject map having the subject values arrayed in N dimensions (N is an integer of 1 or more); generate a subject vector expressing features of a frequency domain of the subject map and random vectors expressing features of respective frequency domains of the shuffle maps; and derive, as an evaluation value for whether the subject map has a random characteristic, a testing result of statistical hypothesis testing on feature differences between the subject vector and the respective random vectors.

Abstract: According to one embodiment, an analysis system includes a display controller. The display controller is configured to display a first comprehensive image and a first individual image from a plurality of workpiece data. The plurality of workpiece data relate to a plurality of workpieces, are classified into a plurality of categories, and are classified into one of a plurality of classes. The first comprehensive image is based on the plurality of workpiece data. The first individual image is based on a part of the plurality of workpiece data classified into one of the plurality of categories.

Abstract: According to one embodiment, an estimation device acquires a data set from history data. The history data includes a plurality of data IDs, path information, first and second qualitative variables. The data IDs respectively indicate a plurality of data flowing through a plurality of nodes. The path information indicates a path of the nodes for each of the data. The first and second qualitative variables are mutually-independent and indicate classifications of each of the data IDs. The data set includes a part of the data IDs having a first variable value assigned as the first qualitative variable. The estimation device estimates an overall relevance indicating a relevancy to the data set for each of the nodes. The estimation device generates a plurality of partial data sets. The estimation device estimates a partial relevance indicating a relevancy to each of the partial data sets for each of the nodes.

Abstract: According to one embodiment, an analysis system includes a display controller. The display controller is configured to display a first comprehensive image and a first individual image from a plurality of workpiece data. The plurality of workpiece data relate to a plurality of workpieces, are classified into a plurality of categories, and are classified into one of a plurality of classes. The first comprehensive image is based on the plurality of workpiece data. The first individual image is based on a part of the plurality of workpiece data classified into one of the plurality of categories.

Abstract: According to one embodiment described herein aim to provide a mobile assist device capable of comprehensively determining (or judging) data output from various sensors, thereby determining (or judging) an item which should be controlled next. The mobile assist device includes a movable body, a sensors mounted on the movable body, and a control module which determines the brightness of the surroundings from an output of the sensor, and also outputs a control signal for controlling the operation of the other instrument based on a result of the determination.

Abstract: According to one embodiment described herein aim to provide a mobile assist device capable of comprehensively determining (or judging) data output from various sensors, thereby determining (or judging) an item which should be controlled next. The mobile assist device includes a movable body, a sensors mounted on the movable body, and a control module which determines the brightness of the surroundings from an output of the sensor, and also outputs a control signal for controlling the operation of the other instrument based on a result of the determination.