Abstract: According to one embodiment, a client device includes a first rule storage unit, a first check execution unit, a user interface control unit, a request transmission unit, and a rule update unit. The rule update unit requests a server device to transmit a rule for updating the first rule storage unit on the basis of a predetermined trigger and updates the first rule storage unit by using the rule transmitted from the server device as a response to the request. The server device has a client rule generation unit. The client rule generation unit generates the client rule to transmit the generated client rule to the client device of a request source when a rule request is received from the rule update unit.

Abstract: An information processing apparatus according to an embodiment includes one or more hardware processors. The hardware processors obtain a first categorical distribution sequence corresponding to first input data and obtain a second categorical distribution sequence corresponding to second input data neighboring the first input data, by using a prediction model outputting a categorical distribution sequence representing a sequence of L categorical distributions for a single input data piece, where, L is a natural number of two or more. The hardware processors calculate, for each i of 1 to L, an inter-distribution distance between i-th categorical distributions in the first and second categorical distribution sequences. The hardware processors calculate a sum of L inter-distribution distances. The hardware processors update the prediction model's parameters to lessen the sum.

Abstract: According to one embodiment, a platooning operation system organizes a platoon by making a plurality of vehicles cooperate. The platooning operation system includes an application acceptance processor and a platoon organization processor. The application acceptance processor accepts an application of a vehicle for admission to the platoon. The platoon organization processor which selects a platoon to which the vehicle is to be admitted or determines possibility of admission of the vehicle to the platoon, based on at least one of information on a driver driving the vehicle and information on the vehicle.

Abstract: According to one embodiment, a platooning operation system organizes a platoon by causing a plurality of vehicles to cooperate on a predetermined route. An application reception processor accepts an application of a vehicle to join to the platoon including at least a designation of a platoon of a plurality of platoons for which a departure time and an arrival time at each point located on the route are preset, and a designation of a departure point and an arrival point on the route. An application management processor performs management of the application including determination on permission of reception of the application such that number of cooperating vehicles in each of the plurality of platoons does not exceed a predetermined number.

Abstract: A virtual try-on system includes one or more hardware processors configured to function as a learning unit, an acquisition unit, a deriving unit, and a generation unit. The learning unit learns, by machine learning using three-dimensional data of a try-on person, a learning model using a teacher try-on person image as input data, and using a body shape parameter indicating a body shape of the try-on person represented by the teacher try-on person image and compositing position information of a clothing image in the teacher try-on person image as output data. The acquisition unit acquires a try-on person image. The deriving unit derives output data of the try-on person represented by the try-on person image using the try-on person image and the learning model. The generation unit generates a virtual try-on image by compositing the try-on person image and the clothing image using the derived output data.

Abstract: According to an embodiment, a reading system includes a reader and a calculator. The reader reads, from a character image, a character that is displayed by a segment display. The calculator performs one of first, second, third, or fourth processing. In the first processing, the calculator calculates a first score based on a state of pixels of the character. In the second processing, the calculator calculates a second score based on a match ratio between the pixels and the extracted pixels. In the third processing, the calculator calculates a third score based on a ratio of a length of the character image in first and second direction. In the fourth processing, the calculator calculates a fourth score based on a comparison result between the detected result and preset patterns. The calculator calculates a certainty of the reading by using one of the first, second, third, or fourth score.

Abstract: According to an embodiment, a reading system includes a first extractor and a reader. The first extractor extracts, from an image in which a meter is imaged, a first region surrounded with a first contour, and a second region surrounded with a second contour positioned outward of the first contour. The reader calculates a first indication based on the first region, calculates a second indication based on the second region, calculates a first score relating to the first indication based on the first region, and calculates a second score relating to the second indication based on the second region.

Abstract: A data processing device according to an embodiment includes a sub-vector group generating unit, a codebook generating unit, and a converting unit. The sub-vector group generating unit generates, from a feature vector set of N number of D-dimensional feature vectors, M number of sub-vector groups (where M<D holds true). Each of the M number of sub-vector groups includes N number of dimension-variable sub-vectors obtained from the N number of D-dimensional feature vectors. For each of the M number of sub-vector groups, the codebook generating unit performs clustering of the N number of dimension-variable sub-vectors, and generates a codebook in which the representative vector of each cluster is associated with an index. The converting unit performs product quantization using the codebook and converts each of the N number of D-dimensional feature vectors into a compressed code made of a combination of M number of indexes.

Abstract: A sound generating device according to an embodiment includes a sound tube and a sound generator. The sound tube is to be held between a tragus and an antitragus. The sound generator is disposed inside the sound tube.

Abstract: An information processing device, an information processing system, an information processing method, and a program capable of appropriately reducing the amount of information of an image are provided. An information processing device includes an image acquisitor, an information amount reduction degree determiner, and an information amount reducer. The image acquisitor acquires an image acquired by imaging an actual space. The information amount reduction degree determiner determines a degree of reduction of an amount of information on the basis of an attribute of a subject shown in the image. The information amount reducer generates information reduced data acquired by reducing at least a part of the amount of information of the image in accordance with the degree of reduction of the amount of information.

Abstract: According to one embodiment, a transport service method comprises organizing a vehicle group of a plurality of self-driving vehicles in which a parameter value inherent to vehicles falls within a predetermined range, and controlling cooperative travel of the self-driving vehicles in the vehicle group to perform transport service of baggage, persons, animals, and the like.

Abstract: According to one embodiment, a learning device includes an acquirer, a generator, a first identifier, an extractor, a second identifier, and a learning-processor. The acquirer acquires real data. The generator generates pseudo data of the real data using a first neural network. The first identifier identifies whether input data is the real data or the pseudo data. The extractor extracts features of data from the input data. The second identifier identifies whether the features extracted by the extractor are features of the real data or features of the pseudo data. The learning-processor learns the first neural network such that the pseudo data and the real data are not discriminated on the basis of an identification result of each identifier.

Abstract: An information display method includes converting P (P?2) high-dimensional data respectively obtained from P images each tagged with a label representing a result of classification into one of a plurality of classes to respectively acquire P low-dimensional data, generating a plot diagram including P plot points obtained by visualizing the P low-dimensional data each depending on the classification result, generating auxiliary information corresponding to a base point set as one of the plot points included in the plot diagram and N (1?N<P) reference points respectively set as the plot points corresponding to the N low-dimensional data extracted from among the low-dimensional data, belonging to a same class as a class to which the base point belongs, among the P low-dimensional data, and generating a display image including the plot diagram to which the auxiliary information is added.

Abstract: According to one embodiment, a skill platform system includes a data acquisition unit, a model creation unit and a skill provision unit. The data acquisition unit is configured to acquire data on work of a skilled worker at a first site. The model creation unit is configured to perform modeling a skill of the skilled worker using the data acquired by the data acquisition unit. The skill provision unit is configured to provide the skill of the skilled worker to a second site by using the model created by the model creation unit.

Abstract: A data processing apparatus according to an embodiment includes a data acquisition unit, a setting unit, and a reinforcement learning unit. The data acquisition unit acquires graph-structured data describing a connection relation between nodes. The setting unit sets a first network representing the graph-structured data acquired by the data acquisition unit. The reinforcement learning unit derives a parameter of the first network such that a feature quantity of an output layer of an evaluation target node in the first network approaches a reward and a feature quantity of an output layer of an operation node becomes a feature quantity causing the feature quantity of the output layer of the evaluation target node to approach the reward.

Abstract: A mold temperature control system includes: an inference model generating portion configured to, based on a plurality of pieces of thermo image data of a mold acquired at predetermined intervals and pieces of teaching data associated with the plurality of pieces of thermo image data, learn a predetermined number of consecutive pieces of time-series image data extracted from the plurality of pieces of thermo image data as one piece of sample data to generate an inference model for detecting a sign of a temperature anomaly of the mold; a mold temperature anomaly degree inference portion configured to detect occurrence of the sign of the temperature anomaly of the mold the predetermined number ahead, using the inference model, based on the predetermined number of pieces of time-series image data of the mold; and a warning lamp request transmitting portion configured to control lighting-up of a warning lamp.

Abstract: According to one embodiment, a processor calculates values of variables in each step of a repetitive calculation using values of the variables calculated in a previous step, and determines whether a difference between the values of the variables calculated in each step and a particular value is larger than a first value. The processor corrects a value of the variables calculated in the previous step to be close to the particular value and calculates a value of the variables in the current step using a corrected value of the variables if the difference is larger than the first value.

Abstract: Disclosed is a service providing system capable of providing an information processing function effective for a variety of system constructions as a service. The service providing system of the present embodiment realizes an information retrieval function, a knowledge base construction function, and a knowledge presentation function. The information retrieval function retrieves information on an analysis target and information indicating a condition of the analysis target; the knowledge base construction function constructs a knowledge database for acquiring knowledge corresponding to the condition of the analysis target based on the information retrieved by the information retrieval function. The knowledge presentation function presents knowledge corresponding to the condition of the analysis target from the knowledge database.

Abstract: An interactive processing device according to an embodiment acquires one/more items' information for predetermined operation through interaction with a user, and includes one/more itemized-processing-units and an interaction-control-unit. The itemized-processing-units corresponds to the items. The interaction-control-unit controls the interaction collaboratively with the itemized-processing-units. The interaction-control-unit transmits user-input information to each itemized-processing-unit. Each itemized-processing-unit extracts a candidate for to-be-acquired information and transmits the candidate to the interaction-control-unit with likelihood information of being the to-be-acquired information. The interaction-control-unit determines a candidate having first-threshold-satisfying likelihood as information of an item corresponding to the candidate-transmitted itemized-processing-unit. When undetermined information item exists, the interaction-control-unit outputs inquiry for the item information.

Abstract: A visualization system includes: a first creation section configured to create, for each product manufacturing unit, a line segment connecting a start or end time of a first step to a start or end time of a subsequent second step; a second creation section configured to identify, based on a change log of a step characteristic factor at each manufacturing step, any change in step characteristic factor observed at the first and second steps, and to create a display object representing magnitude of the change in step characteristic factor or including a region representing an attribute of the changed step characteristic factor; and a display control section configured to cause: to display a line segment representing the time axis, created by the first creation section, and the display object, and to display the display objects over positions of the start or end times on time axes of their associated steps.