Abstract: A learning apparatus configured to be able to communicate with a plurality of equipment in which learning models are mounted, wherein when first equipment among the plurality of equipment in which a learning model trained using training data sets acquired in a predetermined first area is mounted and which is controlled by the same is used in a predetermined second area, the learning apparatus uses training data sets acquired in the second area to relearn the learning model mounted in the first equipment.

Abstract: Disclosed is a wavelength conversion film including at least two or more dyes and absorbing irradiation light to emit light at a longer wavelength than that of the irradiation light. The wavelength conversion film includes a first dye having a maximum absorption wavelength in a red light region, and a second dye absorbing excitation energy of the first dye to emit light in a near infrared region.

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 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 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 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: Provided is a wavelength conversion film containing a luminescent dye, wherein, in an absorption spectrum and an emission spectrum, when the spectrums are normalized so that two maximum intensities of an absorption band having a maximum absorption wavelength of a maximum intensity and an emission band having a maximum emission wavelength of a maximum intensity become the same intensity, and when a molar extinction coefficient at an intersection where the normalized absorption band and the normalized emission band overlap in the spectrum is ?, and a content of the luminescent dye included according to a film thickness per 1 cm2 of the wavelength conversion film is C (mol), the wavelength conversion film satisfies the following Expression (1), 1.0×10?3??×C.

Abstract: An infrared-emitting compound has a structure represented by the following Formula (1a). In Formula (1a), Ar and ring A each independently represent an aryl ring, a heteroaryl ring or a fused ring thereof. Q-Ar represents an infrared-emitting residue. R1 represents a group in which a dihedral angle between Ar and ring A is 45 degree or more. And a thick line represents a single bond or a double bond.

Abstract: Disclosed is a reflective photoplethysmogram sensor comprising: a planar light emitting element and a planar light receiving element. The light emitting element and the light receiving element do not face each other in an up/down direction. The minimum distance h (mm) between at least a pair of the light emitting element and the light receiving element satisfies the following expression (1) (t×03.7)2?h?(t×1.3)2 ??Expression (1) where the minimum distance between the light emitting element and the light receiving element is h (mm), and a thickness of skin (epidermis+dermis) of a human body is t (mm), and the thickness is within the range 0.1 to 4 mm.

Abstract: Disclosed is a wavelength conversion film including at least two or more dyes and absorbing irradiation light to emit light at a longer wavelength than that of the irradiation light. The wavelength conversion film includes a first dye having a maximum absorption wavelength in a red light region, and a second dye absorbing excitation energy of the first dye to emit light in a near infrared region.

Abstract: A learning apparatus configured to be able to communicate with a plurality of equipment in which learning models are mounted, wherein when first equipment among the plurality of equipment in which a learning model trained using training data sets acquired in a predetermined first area is mounted and which is controlled by the same is used in a predetermined second area, the learning apparatus uses training data sets acquired in the second area to relearn the learning model mounted in the first equipment.

Abstract: Provided is a light emitting member that emits near-infrared light, containing a surface light source that emits at least red light and a wavelength conversion film that converts visible light of the surface light source into near-infrared light, wherein the light emitting member has a maximum emission wavelength in the wavelength range of 700 to 1500 nm.

Abstract: A model learning system includes a server and a plurality of vehicles. The server is configured so that when a model differential value showing a degree of difference before and after learning of a learning model used in one vehicle among the plurality of vehicles and trained based on training data sets acquired within a predetermined region is greater than or equal to a predetermined value, it instructs relearning of a learning model used in another vehicle among the plurality of vehicles present in that predetermined region to that other vehicle.

Abstract: A server including a processor configured to: receive a data set from a vehicle; create a plurality of learned models of different scales by performing machine learning using the data set; receive from the vehicle information on computing power of an electronic control unit that controls the vehicle by applying the learned model; and transmit the learned model to the vehicle, wherein the processor is configured to transmit the learned model of a larger scale to the vehicle equipped with the electronic control device having high computing power, than to the vehicle equipped with the electronic control device having low computing power.

Abstract: A vehicle includes a first communication device configured to communicate with a server that correlatively stores trained models of other vehicles and information relating to training conditions of the models of the other vehicles, and a first control device. The first control device is configured to transmit information relating to training conditions of a model of an own vehicle to the server. The first control device is configured to receive part of a model of a particular vehicle of which training conditions are closest to those of the model of the own vehicle, which has been selected from the models of the other vehicles stored in the server, as transfer-learning data. The first control device is configured to reuse part of the received model of the particular vehicle and perform training of the model of the own vehicle.

Abstract: A vehicle allocation device allocates a vehicle in response to a vehicle allocation request from a terminal of a user. The vehicle allocation device includes a vehicle selection unit configured to select a vehicle having relatively small learning progress of an input/output relationship of parameters depending on a scheduled traveling area where the user is traveling, from a plurality of vehicles learning an input/output relationship of parameters depending on a predetermined area, and output a vehicle allocation instruction to the selected vehicle in a case where the vehicle allocation request is received.

Abstract: A compression molded core contains a plurality of soft magnetic material powders. A first powder and a second powder in the plurality of powders satisfy D1>D2, 0.23?(D1?D2)/D1<0.6, D1?7 ?m, and 3 ?m?DT?5.7 ?m. D1 is the median diameter, which is a particle size at which the integrated particle diameter distribution from the small particle size side is 50% in a volume-based particle size distribution measured by a laser diffraction/scattering method, of the first powder and is maximum among median diameters; D2 is the median diameter D2 of the second powder and is minimum among median diameters; and DT is determined using the weight rate R1 of the first powder and the weight rate R2 of the second powder by R1×D1+R2×D2.

Abstract: In a coil-embedded dust core constituting an inductance element, a winding body of a coil disposed inside a coil-embedded dust core and a dust core have a relationship that the inner core volume ratio RV defined below is 3 or more and 5 or less: RV=(V1/V2)/(1?V/Vp), where V1 represents a volume of a region in the dust core located on an inner side of the winding body of the coil when the coil-embedded dust core is viewed in a first direction, which is a direction along a winding axis of the coil, V2 represents a volume of a region in the dust core located on an outer side of the winding body of the coil when the coil-embedded dust core is viewed in the first direction, V represents a volume of the dust core, and Vp represents a volume of the coil-embedded dust core.