Fujitsu

An information processing program causes a computer to execute a process including, in a machine learning model configured to have layers, an input of quantum data being accepted at a first layer, a preceding layer of two consecutive layers included in the layers inputting an output generated by the generation function based on an output of the quantum circuit to the quantum circuit included in a subsequent layer, inputting first quantum data to the first layer and causing first output data to be generated, and inputting, in each second layer arranged in a subsequent stage to the first layer, second quantum data to a quantum circuit that has generated a quantum feature map for an output from a layer arranged in a preceding stage of each second layer, and causing second output data to be generated.

A processing unit identifies a first joint element from a first patch element group included in a first patch that appears in the course of lattice surgery, performs an optimization process for optimizing an application order of controlled NOT (CNOT) gates for a syndrome measurement circuit in the first joint element with respect to a direction of a logical operator defined for the first joint element, and stores, in a storage unit, optimal circuit information associating the first joint element with the application order of CNOT gates. The processing unit identifies, upon detecting a second path during execution of lattice surgery, a second joint element corresponding to the first joint element from a second patch element group included in the second patch, and assigns the application order of CNOT gates associated with the first joint element to the second joint element, based on the optimal circuit information.

An information processing apparatus (100) classifies time-series frames into a plurality of clusters by executing clustering on the time-series frames based on feature amounts of the time-series frames, the time-series frames being included in a moving image belonging to a class of a real moving image or a class of a fake moving image, extracts a concept from each of the plurality of clusters, determines whether the concept extracted from the plurality of clusters is a concept specific to the class or a concept specific to the cluster, sets a weight to the plurality of clusters based on the determination result, and trains a model for estimating a class of a target moving image based on a frame selected based on weights set for the plurality of clusters.

An information processing program causes a computer to execute a process including acquiring video having a scan area of a self-checkout terminal for scanning a barcode of a product analyzing the acquired video to detect an action of a user holding a plurality of products in the scan area of the self-checkout terminal setting either the self-checkout terminal or a management terminal that monitors the self-checkout terminal as a terminal to be notified based on an analysis result of a type of an overlapping state of the plurality of products when the action of the user holding the plurality of products is detected generating alert image information corresponding to the type of the overlapping state of the plurality of products; and causing the generated alert image information to be displayed on a display screen of the terminal set as a notification destination.

Methods and systems for geospatial climate profiling are disclosed. According to an aspect of an embodiment, a method includes obtaining first real-time observational data corresponding to current weather conditions in or near a specified location. The first real-time observational data is obtained based on the first real-time observational data corresponding to surface observations in, on or near the specified location. A virtual weather surveillance image (WSR) image of the specified location is generated using an artificial intelligence (AI) radar image generation model and based on the first real-time observational data. The method can further include generating one or more climate profiles for the specified location based on the virtual WSR image, the first real-time observational data, and one or more contemporaneous satellite images of the specified location.

A computer-implemented method for traffic simulation, the method comprising: accepting input of traffic data for a geographic area; executing a traffic simulation, wherein the traffic simulation comprises a main model configured to progress a traffic system through timesteps, and a sub model configured to perform an ancillary traffic simulation function for a later timestep using traffic data corresponding to an earlier timestep; and outputting a status of the traffic system.

Provided is an estimation method including generating a probability model for estimating a probability that a prospective purchaser changes purchase from a first commodity to a second commodity based on prices of the first commodity and the second commodity, a price change amount of the second commodity, and information indicating whether a purchaser has actually changed the purchase from the first commodity to the second commodity according to price change of the second commodity (S5), and calculating an estimated number of purchases of each of the first commodity and the second commodity based on the probability model (S6).

A computer-implemented method comprising: generating, using a large language model, LLM, and based on information describing a threat to a network, an attack graph, wherein the attack graph comprises nodes corresponding to attack steps and directed edges connecting the nodes; obtaining preliminary attack implementations based on the attack steps in the attack graph, respectively, each preliminary attack implementation comprising code for executing the attack step concerned; assigning, based on information about the network, values to parameters in the preliminary attack implementations to generate objective attack implementations; running an attack on the network or on a simulation of the network by carrying out the objective attack implementations; and outputting a report comprising information indicating outcomes of carrying out the objective attack implementations.

A method for synthetic data generation, the method comprising: accepting input of a target geographic region; acquiring aggregated demographic data for the target geographic region; generating a synthetic population based on the aggregated demographic data using iterative proportional fitting; acquiring infrastructure information for the target geographic region; assigning the synthetic population to a plurality of households using the infrastructure information, thereby forming synthetic population data; outputting the synthetic population data for further use.

According to an aspect of an embodiment, operations may include generating a first representation of a first event of a process flow corresponding to an incident. A second representation of a second event that may be a prediction of a future event to follow the first event in the process flow may be generated based on the first representation using an artificial intelligence model. A third representation of a third event that may be a prediction of a future event to follow the second event in the process flow may be generated based on the first representation and the second representation using the artificial intelligence model. A predicted event sequence for the entire process flow may be generated based on an order of the first event, the second event, and the third event as predicted.