Abstract: The machine learning device comprises a training part configured to train a machine learning model used in a vehicle; and a detecting part configured to detect replacement of a vehicle part mounted in the vehicle. The training part is configured to retrain the machine learning model using training data sets corresponding to a vehicle part after replacement when a vehicle part relating to input data of the machine learning model is replaced.

Abstract: A vehicle allocation device includes a processor including hardware, the processor being configured to: determine, for each vehicle, a necessity of suppressing lowering of performance of an internal combustion engine based on vehicle information corresponding to the vehicle; determine a reservation as a first reservation when reservation information corresponding to the reservation of renting the vehicle satisfies a first condition under which suppressing of lowering of the performance is expected; and allocate the vehicle to the reservation based on the reservation information, wherein the processor is configured to allocate, in a case where the reservation is the first reservation, the vehicle satisfying a second condition indicating a high necessity of the suppression of lowering of the performance or the vehicle having a higher necessity of the suppression of lowering of the performance than the other vehicle to the reservation.

Abstract: A substrate processing apparatus includes first processors, second processors, a transfer module and a controller. Each of the first processors is configured to perform a first processing on a substrate. Each of the second processors is configured to perform a second processing on the substrate on which the first processing is performed. The transfer module is configured to transfer the substrate to the first processors and the second processors. The controller is configured to control the first processors, the second processors and the transfer module. The controller controls a start timing for a first transfer processing of transferring the substrates to the first processor such that a timing of a second transfer processing of transferring the substrate having a liquid film formed thereon to the second processor from the first processor and a timing when another substrate is transferred by the transfer module are not overlapped with each other.

Abstract: A processing apparatus includes a holder configured to hold a substrate; a grinding device configured to perform a grinding on a processing surface of the substrate held on the holder; a transfer device configured to transfer the substrate to the holder; and a controller configured to control the holder, the grinding device and the transfer device. The controller controls the holder, the grinding device and the transfer device to perform performing initialization of the holder, initialization of the grinding device and initialization of the transfer device after the processing apparatus is stopped during an operation thereof and the processing apparatus is restarted; detecting the substrate on the holder; deciding whether the grinding on the detected substrate by the grinding device is required; and performing, by the grinding device, the grinding on the processing surface of the substrate on which the grinding is decided to be required.

Abstract: A notification device in a vehicle enables a person outside the vehicle to be notified of a predetermined operating state of the vehicle by the light emission, and includes: a plurality of spot-shaped light sources arranged at intervals to follow an upper edge of a windshield; a reflecting part reflecting light from the light sources to a front; an outer lens transmitting therethrough the light heading toward the front from the reflecting part; and a housing. The outer lens has on at least one of front and rear faces thereof a fine concave-convex face diffusing the light transmitted through the outer lens. Accordingly, the device is visible through an upper part of the windshield from a person outside the vehicle so that visibility is very good, and the light from the relatively small spot-shaped light source can be sufficiently diffused so that visibility can be further enhanced.

Abstract: A setting method of a protective component includes a resin supply step of supplying a thermoplastic resin to a flat support surface of a support table, and a protective component forming step of shaping the thermoplastic resin into a sheet shape through pressing and spreading the thermoplastic resin along the support surface while heating and softening the thermoplastic resin to form a protective component of the thermoplastic resin in the sheet shape on the support surface. The setting method includes also a protective component bonding step of bringing a front surface that is one surface of the workpiece into tight contact with one surface of the protective component in the sheet shape and heating the protective component in tight contact to bond the protective component to the workpiece, and a post-bonding cooling step of cooling the protective component heated in the protective component bonding step.

Abstract: A machine learning device of an amount of unburned fuel using a neural network in which the correlation functions showing correlations between parameters and an amount of unburned fuel are found for parameters relating to operation of an internal combustion engine, and the parameters with strong degrees of correlation with the amount of unburned fuel exhausted from the engine are selected from among the parameters based on the correlation functions. The amount of unburned fuel is learned by using the neural network from the selected parameters and amount of unburned fuel.

Abstract: A learning use data set showing relationships among an engine speed, an engine load rate, an air-fuel ratio of the engine, an ignition timing of the engine, an HC or CO concentration of exhaust gas flowing into an exhaust purification catalyst and a temperature of the exhaust purification catalyst is acquired. The acquired engine speed, engine load rate, air-fuel ratio of the engine, ignition timing of the engine, and HC or CO concentration of the exhaust gas flowing into the exhaust purification catalyst are used as input parameters of a neural network and the acquired temperature of the exhaust purification catalyst is used as training data to learn a weight of the neural network. The learned neural network is used to estimate the temperature of the exhaust purification catalyst.

Abstract: A learning use data set showing relationships among an engine speed, an engine load rate, an air-fuel ratio of the engine, an ignition timing of the engine, an HC or CO concentration of exhaust gas flowing into an exhaust purification catalyst and a temperature of the exhaust purification catalyst is acquired. The acquired engine speed, engine load rate, air-fuel ratio of the engine, ignition timing of the engine, and HC or CO concentration of the exhaust gas flowing into the exhaust purification catalyst are used as input parameters of a neural network and the acquired temperature of the exhaust purification catalyst is used as training data to learn a weight of the neural network. The learned neural network is used to estimate the temperature of the exhaust purification catalyst.

Abstract: A control support device which supports control of an apparatus by using a learned model by machine learning, includes: a data acquisition unit acquiring an input/output data set which are data relating to an internal or external state of the apparatus and including input parameters and an output parameter of the learned model; a learning unit generating a learned model by performing the machine learning using the input/output data set acquired by the data acquisition unit; and a determination unit determining a learned model which is to be used for the control from among a plurality of learned models, which include a learned model having been completely generated and can be used for the control, based on the input parameters acquired by the data acquisition unit and a learning situation of the machine learning in the learning unit.

Abstract: A package substrate cutting jig table for use in cutting a package substrate is provided. The jig table includes a jig base and a holding member adapted to be detachably mounted on the jig base. The holding member includes a holding surface for holding the package substrate, a plurality of escape grooves formed on the holding surface for preventing the interference of a cutting blade with the holding member, the escape grooves corresponding to a plurality of division lines formed on the package substrate, and a plurality of suction holes formed in a plurality of separate regions defined by the escape grooves on the holding surface. The holding member is formed of a material having a dynamic viscoelastic modulus ranging from 0.16 to 0.41.

Abstract: A substrate processing apparatus includes first processors, second processors, a transfer module and a controller. Each of the first processors is configured to perform a first processing on a substrate. Each of the second processors is configured to perform a second processing on the substrate on which the first processing is performed. The transfer module is configured to transfer the substrate to the first processors and the second processors. The controller is configured to control the first processors, the second processors and the transfer module. The controller controls a start timing for a first transfer processing of transferring the substrates to the first processor such that a timing of a second transfer processing of transferring the substrate having a liquid film formed thereon to the second processor from the first processor and a timing when another substrate is transferred by the transfer module are not overlapped with each other.

Abstract: A machine learning device of an amount of unburned fuel using a neural network in which the correlation functions showing correlations between parameters and an amount of unburned fuel are found for parameters relating to operation of an internal combustion engine, and the parameters with strong degrees of correlation with the amount of unburned fuel exhausted from the engine are selected from among the parameters based on the correlation functions. The amount of unburned fuel is learned by using the neural network from the selected parameters and amount of unburned fuel.

Abstract: A learning use data set showing relationships among an engine speed, an engine load rate, an air-fuel ratio of the engine, an ignition timing of the engine, an HC or CO concentration of exhaust gas flowing into an exhaust purification catalyst and a temperature of the exhaust purification catalyst is acquired. The acquired engine speed, engine load rate, air-fuel ratio of the engine, ignition timing of the engine, and HC or CO concentration of the exhaust gas flowing into the exhaust purification catalyst are used as input parameters of a neural network and the acquired temperature of the exhaust purification catalyst is used as training data to learn a weight of the neural network. The learned neural network is used to estimate the temperature of the exhaust purification catalyst.

Abstract: A substrate processing unit 14 includes processing modules 2 each performing a process on a substrate, and a substrate transfer device 121 is provided between a mounting unit 11 and the processing modules. A parameter storage unit 3 stores sets of transfer parameter 33 where an operating speed of the substrate transfer device corresponds to a processing number of substrates per a unit time. A parameter selecting unit 4 compares a processing number of substrates per a unit time determined based on a recipe 31 corresponding to the process, with those corresponding to the transfer parameters and selects a transfer parameter corresponding to the minimum processing number of substrates among the processing numbers of substrates equal to or larger than that determined based on the recipe. A transfer control units 151 to 153 control the substrate transfer device based on a set value of the selected transfer parameter.

Abstract: An end surface of each first side wall, an end surface of each first middle wall, and an end surface of each first end wall are joined to an adjacent second structure by diffusion bonding, an end surface of each second side wall, an end surface of each second middle wall, and an end surface of each second end wall are joined to an adjacent first structure or a lid structure by diffusion bonding, a thickness of each first side wall is greater than or equal to a thickness of each first middle wall, and a thickness of each second side wall is greater than or equal to a thickness of each second middle wall.

Abstract: A package substrate cutting jig table for use in cutting a package substrate is provided. The jig table includes a jig base and a holding member adapted to be detachably mounted on the jig base. The holding member includes a holding surface for holding the package substrate, a plurality of escape grooves formed on the holding surface for preventing the interference of a cutting blade with the holding member, the escape grooves corresponding to a plurality of division lines formed on the package substrate, and a plurality of suction holes formed in a plurality of separate regions defined by the escape grooves on the holding surface. The holding member is formed of a material having a dynamic viscoelastic modulus ranging from 0.16 to 0.41.

Abstract: An end surface of each first side wall, an end surface of each first middle wall, and an end surface of each first end wall are joined to an adjacent second structure by diffusion bonding, an end surface of each second side wall, an end surface of each second middle wall, and an end surface of each second end wall are joined to an adjacent first structure or a lid structure by diffusion bonding, a thickness of each first side wall is greater than or equal to a thickness of each first middle wall, and a thickness of each second side wall is greater than or equal to a thickness of each second middle wall.

Abstract: A disposable diaper includes a waist opening and a pair of leg openings with a composite stretchable member. The composite stretchable member includes first and second nonwoven fabric sheet parts and elastic members arranged therebetween. Each of the first and second nonwoven fabric sheet parts is provided with a plurality of convex-concave regions including convex and concave parts. At least one non-shaped region separates the convex-concave regions from each other in the longitudinal direction. The first and second nonwoven fabric sheet parts are overlaid so that the convex-concave regions of the first nonwoven fabric sheet part and the second nonwoven fabric sheet part adjoin each other and the non-shaped regions of the first nonwoven fabric sheet part and the second nonwoven fabric sheet part are separated from each other and are joined with each other by an adhesive applied to the elastic members.

Abstract: Provided is a substrate processing apparatus which can efficiently transfer substrates using a conveying mechanism including a plurality of substrate holding members. The substrate processing apparatus transfers a processed substrate to an intermediate conveying unit using a transport mechanism when the processed substrate returns to a substrate receiving unit.