Abstract: A communication assistance program is a communication assistance program assisting communication of a user, the communication assistance program causing a computer to perform a step of integrally displaying identification information that can be used for identifying a communication target and a state animation representing a state of the communication target.

Abstract: A communication assistance program is a communication assistance program assisting communication of a user, the communication assistance program causing a computer to perform a step of integrally displaying identification information that can be used for identifying a communication target and a state animation representing a state of the communication target.

Abstract: A communication assistance system according to one embodiment is a communication assistance system assisting communication performed by a user using a terminal, the communication assistance system includes a control data configured to generate unit generating control data for controlling a movement of an avatar of the user that is displayed on the terminal and participates in the communication, based on video data including voice data of the user and image data of the user, when there is a deficiency of image information in the image data of the user, the control data generating unit supplements a deficient image information by using the voice data of the user and a learned model, and the learned model is a learned model generated by using training data such that the control data of the avatar is output when the voice data of the user is input.

Abstract: A communication assistance system according to one aspect of the present disclosure assists communication between a first user corresponding to a first terminal and a second user corresponding to a second terminal. The communication assistance system includes at least one processor. The at least one processor receives video data representing the first user from the first terminal, analyzes the video data and selects a movement pattern corresponding to a non-verbal behavior of the first user from a movement pattern group of an avatar, and transmits control data indicating the selected movement pattern to the second terminal such that an avatar corresponding to the first user in a virtual space displayed on the second terminal is moved based on the selected movement pattern.

Abstract: A communication assistance system according to one aspect of the present disclosure assists communication between a first user corresponding to a first terminal and a second user corresponding to a second terminal. At least one processor of the system analyzes first video data representing the first user and selects a movement pattern corresponding to a first non-verbal behavior that is a non-verbal behavior of the first user from a movement pattern group of an avatar, and transmits control data indicating the selected movement pattern to the second terminal. The second terminal displays a virtual space including a first avatar corresponding to the first user and a second avatar corresponding to the second user on the second terminal, receives the control data, moves the first avatar based on the selected movement pattern, and moves the second avatar based on second video data representing the second user.

Abstract: A vehicle malfunction prediction system includes: one or more monitoring devices, each monitoring device obtaining from a functional unit in a vehicle in which the monitoring device is mounted, functional-unit information indicating a result of measurement related to the vehicle; and a management device. The monitoring device transmits the obtained functional-unit information to the management device via an external network. The management device creates a learning model based on machine learning on the basis of a plurality of pieces of functional-unit information received from the one or more monitoring devices and transmits the created learning model to the one or more monitoring devices. Each monitoring device predicts a malfunction in the vehicle in which the monitoring device is mounted on the basis of new functional-unit information from the functional unit in the vehicle in which the monitoring device is mounted and based on the learning model from the management device.

Abstract: Provided is a microscope device which includes: (1) a light source that outputs illumination light in a wavelength band including a near-infrared region; (2) an illumination optical system that irradiates an observation target with the illumination light output from the light source; (3) an image formation optical system that includes a spectroscopic unit which is configured to receive and disperse transmitted or scattered light produced at the observation target by irradiating the observation target with the illumination light, and that forms an image on the basis of the dispersed transmitted or scattered light; and (4) an image capturing unit that acquires the image formed by the image formation optical system. An illumination-light-irradiated area of the observation target is larger than an area of the field of view of the image formation optical system, and is less than or equal to ten times the area of the field of view.

Abstract: A quality evaluation method includes an acquisition step of acquiring spectral data related to transmitted light or diffusely reflected light from a cell mass by irradiating the cell mass with measurement light including near-infrared light, and an evaluation step of evaluating quality of the cell mass, based on the spectral data of the cell mass acquired in the acquisition step.