Abstract: An information processing method includes: creating a first table by an experimental design method, calculating a first response surface using the first table, setting a fourth level value for a first control factor when the first response surface does not include a target value related to an object variable for the first control factor, creating a second table by the experimental design method by deleting at least one combination of the experimental conditions which include one level value for the first control factor from the first table and adding at least one combination of the experimental conditions based on the plurality of level values including the fourth level value and without including the one level value for the first control factor, calculating a second response surface including the target value using the second table, and outputting the second response surface.

Abstract: Data analysis device (1) includes data acquisition unit (10) that acquires a plurality of explanatory variables X and E and objective variable Y that can take different values depending on a time, first model derivation unit (30) that performs multiple regression analysis by using the plurality of explanatory variables X and E and objective variable Y and derives first model M1 indicating a relationship between the plurality of explanatory variables X and E and objective variable Y, change point detection unit (50) that detects change point Tc that is a time when a predetermined explanatory variable (for example, E) among the plurality of explanatory variables X and E changes beyond a predetermined range, and second model derivation unit (60) that corrects first model M1 based on predetermined explanatory variable E starting from change point Tc and derives second model M2 that is a corrected model.

Abstract: Evaluation device (100) is a device that evaluates, by Bayesian optimization, unknown characteristic points corresponding to a plurality of candidate control points at a second time following a first time based on known characteristic points corresponding to controlled control points at the first time, the device including: reception controller (10) that acquires control result data (222) indicating the controlled control points at the first time and the known characteristic points at the first time, purpose data (212) indicating an optimization purpose, constraint condition data (213) indicating a constraint condition, and region reduction rule data (214); evaluation value calculating unit (12) that calculates an evaluation value of each of the plurality of unknown characteristic points based on control result data (222), purpose data (212), constraint condition data (213), and region reduction rule data (214); and evaluation value output unit (13) that outputs an evaluation value.

Abstract: An experiment of processing a device is performed to acquire type 1 information and type 2 information indicating processing conditions, and type 3 information and type 4 information indicating results of the processing, derive a first relation between the type 1 information, the type 2 information, and the type 3 information, and a second relation between the type 1 information, the type 2 information, and the type 4 information, and generate and output a model that estimates the type 4 information indicating a result of the processing by using the first relation and the second relation with the type 2 information and the type 3 information that are measured during the processing as inputs.

Abstract: Evaluation device (100A) is a device that evaluates, by Bayesian optimization, an unknown characteristic point corresponding to a candidate experimental point based on a known characteristic point corresponding to an experimented experimental point, the evaluation device including: reception controller (10A) that acquires experimental result data (222) indicating the experimented experimental point and the known characteristic point, objective data (212) indicating an optimization objective, constraint condition data (213) indicating a constraint condition, and region reduction rule data (214); evaluation value calculator (12A) that calculates an evaluation value of the unknown characteristic point based on experimental result data (222), objective data (212), constraint condition data (213), and region reduction rule data (214); and evaluation value output unit (13) that outputs the evaluation value, in which evaluation value calculator (12A) gives a weighting according to a degree of conformity of the const

Abstract: A leaning vehicle including a vehicle body frame, at least one steerable wheel, a handlebar, of which the manipulation by a rider generates a steering torque, a steering actuator steering the at least one steerable wheel, a roll rate sensor detecting a roll rate of the vehicle body frame, and a steering actuator controller. The steering actuator controller includes a torque estimation section that receives an input to thereby generate an estimated value of the steering torque, and a current determination section that obtains a control current based on the estimated valued of the steering torque generated by the torque estimation section, and outputs the control current to the steering actuator to control the steering actuator. The input of the torque estimation section includes the roll rate obtained from the roll rate sensor, but is free from any value of the steering torque detected by a torque sensor.

Abstract: An information processing method includes: creating a first table; calculating a first response surface using the first table in which an object variable is recorded, the object variable acquired when experimental conditions of a first control factor is fixed to a first level value; adding the experimental conditions of the first control factor in which the first level value is set to the first table when the first response surface does not include a target value related to the object variable; creating a second table by adding a plurality of combinations of the experimental conditions for each of the plurality of control factors in which a first plurality of level values are set and the first control factor in which a second plurality of level values are set to the first table; calculating a second response surface including the target value using the second table; and outputting the second response surface.

Abstract: A leaning vehicle including a vehicle body frame that is configured to lean leftward and rightward respectively when the leaning vehicle is turning left and right, a steerable wheel supported by the vehicle frame body, a steering mechanism steering the steerable wheel, and a posture control actuator device. The posture control actuator device includes a posture control actuator that outputs power to control posture of the vehicle body frame, and an angular rate sensor that detects an amount of change per unit time of a rotation angle of the vehicle body frame around a rotation axis thereof, the rotation angle changing as the vehicle body frame is rotating around the rotation axis. The posture control actuator device is supported by the vehicle body frame, and is attachable to and detachable from the vehicle body frame. The posture control actuator and the angular rate sensor are not displaceable relative to each other.

Abstract: A leaning vehicle including a vehicle body, at least one front wheel, at least one rear wheel, a leaning device that causes the vehicle body, the at least one front wheel and the at least one rear wheel to lean leftward or rightward at the left-turn or right-turn of the leaning vehicle, a steering handle rotatable counter-clockwise or clockwise to turn the at least one front wheel left or right, a lean actuator supplying power to the leaning device, and a control unit that controls the lean actuator in accordance with an amount of rotation of the steering handle detected by a steering-handle rotation sensor. The control unit is configured to, when the steering handle is rotated within a particular rotation range, control the lean actuator to restrain the vehicle body, the at least one front wheel and the at least one rear wheel from leaning.

Abstract: Data analysis device 1 includes: a difference value calculator that calculates, in data section (i, i+1) in which ith data at a predetermined date and time among the plurality of pieces of data is used as a start point value and (i+1)th data at a date and time after the predetermined date and time is used as an end point value, explanatory variable difference value ?X that is a difference between start point value X(i) of explanatory variable X included in the ith data and end point value X(i+1) of explanatory variable X included in the (i+1)th data, and target variable difference value ?Y that is a difference between start point value Y(i) of target variable Y included in the ith data and end point value Y(i+1) of target variable Y included in the (i+1) data; and a difference model derivation unit that derives difference model M indicating a relationship between explanatory variable difference value ?X and target variable difference value ?Y based on a plurality of the explanatory variable difference values

Abstract: An information processing method calculates a position of a feature corresponding to a trace in a first coordinate system, calculates a position of the feature corresponding to the trace in a second coordinate system, and calculates a size of a first distribution of the position of the feature corresponding to the trace in the first coordinate system and a size of a second distribution of the position of the feature corresponding to the trace in the second coordinate system. Additionally, the information processing method outputs information indicating that the feature corresponding to the trace is the trace formed on the surface of the workpiece in the machining process, and outputs information indicating that the feature corresponding to the trace is a false detection of the trace in the inspection process.

Abstract: A straddled vehicle, including a vehicle body having a rotatable handlebar; a steerable wheel, operation of which is transmitted mechanically to steer the steerable wheel; an actuator configured to apply a steering assisting force to the steerable wheel in accordance with the operation of the handlebar; and a control device configured to control the actuator by outputting a first physical quantity related to the steering assisting force, in accordance with a second physical quantity related to the operation of the handlebar. The control device performs, in response to an external instruction or fulfillment of a condition, setting or changing a dead band, which is a predetermined range of the second physical quantity in which the first physical quantity is not outputted even with the operation of the handlebar, and/or setting or changing an output increasing range in which as the second physical quantity increases, the outputted first physical quantity increases.

Abstract: A straddled vehicle includes a vehicle body frame, a steering shaft supported by the vehicle body frame, a handlebar that includes a left grip and a right grip and is connected to the steering shaft, a steering wheel, and a steering assist device that applies assist force in a same direction as that of a steering torque that has been input to the handlebar by a rider to the steering shaft. The steering assist device causes the assist force to decrease as speed of the vehicle increases in a first vehicle speed zone and causes the assist force to increase as the speed of the vehicle increases in a second vehicle speed zone that is higher than the first vehicle speed zone.

Abstract: Experimental device machining is performed according to plan information including first type information indicating a first type condition of the experimental device machining and second type information indicating a second type condition of the experimental device machining. Third type information indicating a third type result and fourth type information indicating a fourth type result are acquired. Extended plan information is acquired in which a uniformity of extended second type information and extended third type information is equal to or greater than a threshold value. Extended third type information indicating a third type result and extended fourth type information indicating a fourth type result are acquired by performing the experimental device machining according to the extended plan information. An extended first relationship is derived that is a relationship between extended first type information, the extended second type information, and the extended third type information.

Abstract: An evaluation device is a device that evaluates, by Bayesian optimization, an unknown characteristic point corresponding to a candidate experimental point based on a known characteristic point corresponding to an experimented experimental point, the device including: a reception controller that acquires experimental result data indicating the experimented experimental point and the known characteristic point, objective data indicating an optimization objective, and constraint-condition data indicating a constraint condition; an evaluation value calculator that calculates an evaluation value of an unknown characteristic point based on the experimental result data, the objective data, and the constraint-condition data; and an evaluation value output unit that outputs the evaluation value, in which the evaluation value calculator gives weighting according to a degree of compatibility of the constraint condition to an evaluation value for at least one objective characteristic.

Abstract: A processor performs an experiment of machining a device to acquire first-type and second-type information each indicating conditions of the experiment of machining and third-type and fourth-type information each indicating a result of the experiment of machining (S401). The processor derives a first expression and a second expression, where the first expression receives first-type and second-type information as inputs and outputs third-type information as more than one solution, and the second expression receives first-type and second-type information as inputs and outputs fourth-type information. The processor derives more than one third expression from the first expression, where the more than one third expression each receives second-type and third-type information as inputs and outputs first-type information (S402).

Abstract: A leaning vehicle including a vehicle body, at least one front wheel, at least one rear wheel, a leaning device that causes the vehicle body, the at least one front wheel and the at least one rear wheel to lean leftward or rightward at the left-turn or right-turn of the leaning vehicle, a steering handle rotatable counter-clockwise or clockwise to turn the at least one front wheel left or right, a lean actuator supplying power to the leaning device, and a control unit that controls the lean actuator in accordance with an amount of rotation of the steering handle detected by a steering-handle rotation sensor. The control unit is configured to, when the steering handle is rotated within a particular rotation range, control the lean actuator to restrain the vehicle body, the at least one front wheel and the at least one rear wheel from leaning.

Abstract: A leaning vehicle, including a vehicle body leaning left and right when the leaning vehicle turns left and right, respectively, left and right steerable front wheels that are each steerable by a turning manipulation input device, a rear wheel unsteerable by the turning manipulation input device, a lean actuator that causes the vehicle body to lean, and a control device configured to control the lean actuator. When the left and right steerable front wheels are steered in a first direction while the leaning vehicle is traveling straight backward with the vehicle body being upright, the lean actuator causes the leaning vehicle to turn in the first direction, with a front portion thereof moving farther in a second direction than a rear portion, such that the vehicle body kept upright, where the first and second directions are respectively one and the other of the left and right directions.

Abstract: An information processing method includes a step of calculating a position of a feature corresponding to a trace in a first coordinate system defined with reference to a field of view of an image, a step of calculating a position of the feature corresponding to the trace in a second coordinate system defined with reference to a position of a workpiece recorded in the image, a step of calculating a size of a first distribution of the position of the feature corresponding to the trace in the first coordinate system and a size of a second distribution of the position of the feature corresponding to the trace in the second coordinate system, and a step of outputting information indicating that the feature corresponding to the trace is the trace formed on the surface of the workpiece in the machining process, when a difference between the size of the first distribution and the size of the second distribution exceeds a first predetermined value, and outputting information indicating that the feature corresponding t

Abstract: An information processing method includes: creating a first table; calculating a first response surface using the first table in which an object variable is recorded, the object variable acquired when experimental conditions of a first control factor is fixed to a first level value; adding the experimental conditions of the first control factor in which the first level value is set to the first table when the first response surface does not include a target value related to the object variable; creating a second table by adding a plurality of combinations of the experimental conditions for each of the plurality of control factors in which a first plurality of level values are set and the first control factor in which a second plurality of level values are set to the first table; calculating a second response surface including the target value using the second table; and outputting the second response surface.