Abstract:
It selects learning data that is effective for learning a learning model. An identification information assignment device comprising: a processor; and memory, wherein, using the memory, the processor: acquiring a plurality of image data; selecting a part of the plurality of image data as learning data; assigning identification information to the selected image data by using a learning model which is recorded in the memory; and updating the learning model by using the selected image data to which the identification information is assigned, wherein identification information is assigned to a rest of the plurality of image data by using the updated learning model, the rest of the plurality of image data being different from the selected image data.
Abstract:
A method evaluating a decrease in production performance for a target work. A work efficiency evaluation method includes the steps of: reading, from a storage, model data used for evaluating work efficiency and generated based on operation data related to work including a predetermined work time and a predetermined work amount; calculating an degree of impact of a decrease in work efficiency on the basis of data related to time required for work and a work amount by the model data; and evaluating a decrease in production performance in accordance with the degree of impact.
Abstract:
The prediction device includes a storage storing measure implementation information representative of an effect of the measured on a first target, and a control circuit predicting an effect of the measures on a second target having no measure implemented therein based on the measure implementation information; the control circuit constructs a first graph made up of a plurality of nodes including at least one first node associated with the first target and at least one second node associated with the second target, and a plurality of links connecting the nodes based on a similarity between the nodes; and based on the measure implementation information, the control circuit determines a degree of the effect of the measures on the first node and propagates the degree of the effect of the measures on the second node by using the first node as a base point in the first graph.
Abstract:
A data analysis device, for analyzing efficiency of an assembly line operation including processes, includes: an input interface configured to acquire log data indicating a history of the processes respectively performed for each time of the assembly line operation; and a control circuit configured to generate analysis information indicating an analysis result of the history indicated by the log data, based on information generated by a probability model to calculate probability distribution for the assembly line operation. The probability model is configured to: generate process efficiency distribution indicating probability distribution of efficiency for each process in the assembly line operation, and variation factor distribution indicating probability distribution of a factor probable to vary the efficiency of the assembly line operation in each process; and generate work efficiency distribution indicating probability distribution of the efficiency of the assembly line operation, based on the process efficiency distribution and the variation factor distribution.
Abstract:
A first tabulation device includes a classification ID acquisition unit that acquires classification IDs of consumers, a purchase ID acquisition unit that acquires purchase IDs of products or services, and an analysis unit that tabulates the classification IDs and the purchase IDs, and analyzes first tabulation information indicating distribution of the classification IDs with respect to the purchase IDs. A second tabulation device includes a classification ID generation unit that generates the classification IDs, based on frequency of a predetermined behavior of the consumers, and a calculation unit that calculates second tabulation information indicating distribution of the frequency of the predetermined behavior with respect to a purchase ID, based on the first tabulation information input from the first tabulation device and the classification IDs. The first tabulation device acquires the second tabulation information, allowing tabulation of purchase data with which a correlation between them can be analyzed while maintaining confidentiality.
Abstract:
A quality estimation device for generating information on quality with which a plurality of unit products are obtained by using a plurality of facilities to pass at least one step, includes: a memory that stores quality control data associating the facilities passed for each of the unit products in the step when the unit products are obtained, with quality for the obtained unit products; and a circuit that controls calculation processing based on the quality control data stored in the memory. The circuit extracts a plurality of pass records from the quality control data, the plurality of pass records each indicating a series of facilities passed by a unit product in the plurality of unit products and quality for the unit product, and generates facility quality information indicating quality with respect to a facility in the plurality of facilities by the calculation processing, based on the extracted pass records.
Abstract:
A demand prediction device includes a memory and a processor that, when executing instructions stored in the memory, performs a process which includes acquiring an input variable including delivery date and time, predicting a heat map corresponding to the input variable by using a heat map prediction model for predicting a heat map which indicates, for each segment, the number of distributions of delivery destinations distributed in at least one of a plurality of segments constituting a delivery target area, predicting the minimum number of delivery vehicles corresponding to the predicted heat map by using a minimum delivery vehicle number prediction model for predicting the minimum number of the delivery vehicles for delivering a package to the delivery destination, and determining the predicted minimum number of the delivery vehicles as the number of delivery vehicles at the delivery date and time included in the input variable.
Abstract:
A model generating device according to the present disclosure includes: an acquisition unit that acquires demand information indicative of the number of sales of a product in a shop for a past predetermined period and external information relevant to the number of sales of the product; and a controller that generates a forecasting model for calculating a forecast value of demand for the product based on the demand information and the external information, wherein the controller includes a simulator that simulates the number of displayed pieces of the product based on the demand information and the forecast value and a forecasting model generator that generates the forecasting model based on the external information and the number of displayed pieces of the product and calculates the forecast value by using the forecasting model.
Abstract:
A recommendation image display system includes: a receiving unit which receives content related information items each of which includes a content recommendation level determined based on a content viewing history of a content item obtained from a corresponding one of a plurality of terminals; a generating unit which generates a recommendation image in which a plurality of icons for allowing a user to select one of content items are displayed based on the received content related information; and a display unit which displays the recommendation image. The plurality of icons include a first icon and a second icon indicating a content item having a recommendation level higher than that of the content item indicated by the first icon. The generating unit generates the recommendation image in which the second icon is displayed in the mode in which the second icon is more likely to be selected by the user than the first icon.
Abstract:
A video output device according to the present disclosure synthesizes a plurality of videos into a video to be displayed. The video output device includes image processing unit and output unit. The image processing unit extracts a plurality of reference frames from any one reference video selected from the plurality of the videos captured by an imaging unit, and extracts a corresponding frame, most similar to a respective one of the reference frames, from each of the videos excluding the reference video. The output unit outputs a synthesized frame which image processing unit synthesizes from the each of the reference frame and the corresponding frame.