Abstract: A replacement confirmation system includes: a retaining unit that retains a learning model, which is generated by machine learning and outputs a parameter used for vehicle control; an acquirer that acquires a result of confirmation with a driver of a vehicle regarding permission for replacement of a parameter output function other than a learning model used in vehicle control with a learning model; and a determination unit that determines to perform replacement with a learning model when the acquirer has acquired permission from a driver.

Abstract: A model learning system includes a device in which a learning model is used, a data acquisition device that acquires data used for creating a training data set for the learning model, and a model learning device that automatically learns the learning model using the training data set for the learning model created using the data. The model learning device is configured to, when a model accuracy after automatically learning the learning model decreases or does not increase compared to before learning, exclude the learning model from a target to be automatically learned.

Abstract: A device for predicting power consumption in a predetermined target area includes: an attribute specifying unit for specifying an attribute of a person within the predetermined target area; and a prediction unit for calculating a predicted power consumption in the target area based on the specified attribute such that the predicted power consumption in the target area differs when the attribute of the person differs.

Abstract: A data collection device collects data from a data acquisition device for acquiring data relating to a person located within a predetermined target area. The data collection device includes a processor for: determining whether data acquired by the data acquisition device is data relating to a resident within the target area; and controlling transmission of data from the data acquisition device to the data collection device. The processor causes the data acquisition device to transmit data of parameters that are at least partially different between a case where data acquired by the data acquisition device relates to a resident and a case where data acquired by the data acquisition device does not relate to a resident.

Abstract: A server includes a processor that: acquires a learning condition for newly generating a learned model; identifies AI ethics that the learned model needs to satisfy; and determines whether the learned model newly generated satisfies the AI ethics based on the learning condition and the AI ethics.

Abstract: A server includes a processor that: acquires a learning condition of a learned model; identifies AI ethics that the learned model needs to satisfy; and determines whether the learned model satisfies the AI ethics based on the learning condition and the AI ethics.

Abstract: A data collection system collects data, for training of a machine learning model for classifying into a plurality of classes, from a data acquisition device to a data collection device. The system includes a processor configured to specify an occurrence probability of occurrence of a low occurrence class for each condition; set a target transmission amount per unit time; specify a current condition; and transmit data from the data acquisition device to the data collection device, in accordance with a target transmission amount corresponding to the specified current condition. The amount of data transmission is larger in a condition having a relatively higher occurrence probability of the low occurrence class, compared to a condition having a relatively lower occurrence probability of occurrence of the low occurrence class.

Abstract: A data management device includes an information acquisition unit that acquires information indicating a resident's degree of acceptance of data collection in a residential unit, and a sensor setting unit that determines an activating mode of each of a group of sensors in the residential unit based on the information acquired by the information acquisition unit.

Abstract: A data collection system has a data acquisition device located in a predetermined target area and a data collection device communicable with the data acquisition device, and collects data necessary for use or training of a machine learning model from the data acquisition device to the data collection device. The data collection system includes a processor configured to: determine whether a collection promotion condition is satisfied; and control data transmission. The processor controls data transmission from the data acquisition device to the data collection device so that an amount of data transmission per unit time is larger when it is determined that the collection promotion condition is satisfied, compared to when it is determined that the collection promotion condition is not satisfied.

Abstract: A data collection apparatus collects data used for a process, based on image data representing a group of consecutive images received from an imaging device. A processor of the data collection apparatus is configured to: control transmission of image data to the data collection apparatus; detect an object included in each image of an image group represented by the image data; track a detected object between consecutive images; store object image data relating to each object tracked; and calculate a number of objects included in an image represented by the image data. The control of transmission of the image data or the detection of the objects is performed such that an amount of data per unit number of objects is smaller when the calculated number of objects is relatively larger, as compared to when the number is relatively smaller.

Abstract: A model management device includes a communication execution unit that transmits, when a first machine learning model having an accuracy of a predetermined value or more is generated in a first target area, information about the first machine learning model to at least one target area different from the first target area.

Abstract: A data collection apparatus can communicates with a plurality of terminal devices located in a predetermined target area and respectively held by individuals, and collects data from the terminal devices. The data collection apparatus includes a transmission control unit for controlling transmission of data from the terminal devices; and a calculation unit for calculating the number of the terminal devices located in the target area. The transmission control unit controls transmission of data from the terminal devices so that when the number of the terminal devices located in the target area is relatively large, the transmission speed of data from the terminal devices is slower or the number of the terminal devices stopping transmission of data among the terminal devices located in the target area is larger than when the number of the terminal devices located in the target area is relatively small.

Abstract: A vehicle controller includes a processing unit which creates a power-supply plan that ensures a first amount of electric power needed for the vehicle to arrive at the destination from the current location along a travel route. The travel route includes a specified section on which wireless power-supply equipment, among a plurality of power-supply equipment, is disposed. Using weather information including the specified section, the processing unit creates the power-supply plan in which a ratio of a second amount of electric power, which is supplied from the at least one wireless power-supply equipment to the vehicle, to the first amount of electric power is less in a first case in which deposition is determined to be present on the specified section than in a second case in which deposition is determined to be not present on the at least one specified section.

Abstract: A charging amount calculation apparatus calculates an amount of power consumption by a battery for running along a running route and a during-running charging amount received by a power reception apparatus from at least one second power feeding facility. The charging amount calculation apparatus calculates a pre-running charging amount based on the amount of power consumption and the during-running charging amount.

Abstract: A vehicle information DB holds information on whether or not a vehicle falls under a welfare vehicle provided with an assistance apparatus for a driver who has a lower limb impairment. A power feed facility DB holds position information of a power feed facility and information indicating whether the power feed facility falls under a contact type power feed facility or a wireless power feed facility. A processing apparatus creates a travel route such that a larger number of wireless power feed facilities are included along the travel route when the vehicle falls under the welfare vehicle than when the vehicle does not fall under the welfare vehicle.

Abstract: A processor of a control device of a server for machine learning a plurality of models with different output parameters, comprising a receiving part for receiving information from a plurality of equipment connected to be able to communicate, a learning use data set preparing part for using information which the receiving part receives to prepare a learning use data set for each model, and a learning part for machine learning with priority a model with a high priority order in models for which the number of data sets required for learning have been prepared based on the priority orders of learning among models if the number of data sets required for learning have been prepared for a plurality of models.

Abstract: A substrate processing apparatus 1 includes a controller 61 configured to perform a first recipe and a second recipe in parallel. Each of the first recipe and the second recipe includes a first transfer processing of transferring a substrate from a transit unit 14 to a liquid processing unit 17, a liquid processing, a second transfer processing of transferring the substrate from the liquid processing unit 17 to a drying unit 18 and a drying processing. The controller 61 determines, while the first recipe on a first substrate in substrates is being performed, when the second recipe on a second substrate in the substrates is started, a start timing of the first transfer processing of the second substrate such that a time period of the second transfer processing of the first substrate does not overlap with a time period of the second transfer processing of the second substrate.

Abstract: A server prepares a charging plan for a travel route to a destination. The server obtains an outside air temperature and a battery temperature. The server reads a map from a storage, and calculates an amount of required heat required for increasing the battery temperature to a target temperature by collating the outside air temperature and the battery temperature with the map. The server prepares the charging plan such that an SOC of a battery at the time of arrival at the destination attains to a prescribed SOC and a sum of an amount of heat generation by charging of the battery at a charging point and an amount of heat generation by charging and discharging of the battery with travel of a vehicle is equal to the amount of required heat.

Abstract: A substrate processing method of grinding a first substrate in a combined substrate in which the first substrate and a second substrate are bonded to each other includes measuring a total thickness distribution of the combined substrate; measuring a thickness distribution of the first substrate; calculating a thickness distribution of the second substrate by subtracting the thickness distribution of the first substrate from the total thickness distribution of the combined substrate; deciding a relative inclination between a substrate holder configured to hold the combined substrate and a grinder configured to grind the combined substrate, based on the thickness distribution of the second substrate; and grinding the first substrate while holding the combined substrate at the inclination which is decided.

Abstract: A substrate processing method includes measuring a first thickness distribution of a first substrate in a first one of multiple combined substrates before being subjected to a finishing grinding; measuring a second thickness distribution of the first substrate in a second one of the multiple combined substrates before being subjected to the finishing grinding; deciding a relative inclination between a substrate holder configured to hold the second one of the multiple combined substrates and a grinder configured to perform the finishing grinding on the corresponding combined substrate, based on first difference data between the first thickness distribution and the second thickness distribution; and performing finishing grinding on the first substrate in the second one of the multiple combined substrates while holding the second one of the multiple combined substrates at the inclination which is decided.