Abstract: A non-transitory computer-readable recording medium has stored therein a distribution program that causes a computer to execute a process, the process including, extracting a person and a product from a video of an inside of a store, tracking the extracted person, identifying a behavior that is performed by the tracked person with respect to a product in the store, identifying a first behavior type that is led by the behavior that is performed by the tracked person with respect to the product among a plurality of behavior types that define transition of a process of the behavior since entrance into the store until purchase of a product in the store, and distributing information on a product indicating the first behavior type to the tracked person when the identified first behavior type is at a predetermined level or higher and the tracked person has not yet purchased the product.

Abstract: A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: acquiring at least one of time points of start or end of each elemental action related to an action specified on a basis of a moving image of the action; and generating information that enables specification of a time in which the action has been performed on a basis of the acquired time point with reference to a rule that provides at least one of a logical condition for the elemental action related to the action or an order condition between the elemental actions related to the action, the logical condition or the order condition being satisfied in a case where the action is performed.

Abstract: A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: acquiring data that indicates a relationship between element actions for a plurality of element actions in an object period; acquiring an effective time that corresponds to an object action; and searching for a combination of two or more element actions that form the object action among the plurality of element actions for each divided section set by dividing the object period according to the acquired effective time on the basis of the acquired data.

Abstract: A machine learning method includes: generating, by a computer, a sine wave using a basic period of input data having a periodic property; determining a sampling period based on a degree of roundness of an attractor generated from the sine wave; sampling the input data at the determined sampling period to generate a pseudo attractor; and performing a machine learning by using the pseudo attractor.

Abstract: A distance measurement apparatus of a scanning type provided with a two-dimensional micro electro mechanical system (MEMS) mirror that reflects a laser beam includes: a first detector that detects a mirror angle of the two-dimensional MEMS mirror and outputs an angular signal that indicates the mirror angle; and a processor that calculates an amplitude error and a phase error between amplitude and a phase of the angular signal and amplitude and a phase of a reference angle signal, and corrects a resonance drive waveform of a drive signal that drives, of two mutually orthogonal axes of the two-dimensional MEMS mirror, one axis on a resonance drive side on a basis of the amplitude error and the phase error.

Abstract: An apparatus obtains time series data to which a label indicating a category of classification is attached, where the time series data contains variations of target values during a period to which the label is attached. The apparatus divides the time series data into a plurality of sections, and generates an attractor for each of the plurality of sections where the attractor indicates a set of numerical values toward which the variations of the target values tends to evolve. The apparatus calculates a Betti sequence in accordance with the generated attractor for each of the plurality of sections, and obtains a feature for the Betti sequences of the plurality of sections by clustering the Betti sequences or by calculating a statistical quantity of the Betti sequences. The apparatus performs machine learning by using the obtained feature as an input.

Abstract: A detection device generates plural attractors based on brainwave data. Subsequently, the detection device calculates a Betti number by subjecting the attractors to persistent homology transform. The detection device determines an onset of encephalopathy based on a first order component of a Betti sequence calculated based on the Betti number.

Abstract: A noise determination method executed by a computer, the noise determination method includes: acquiring time-series data; identifying a shape of a waveform of the time-series data using a persistent diagram; extracting a cluster whose lifetime from birth to death is equal to or greater than a threshold value in the persistent diagram; determining, from statistical information regarding time intervals related to pieces of data included in the cluster, whether or not peaks appear at regular intervals in the waveform of the time-series data; and controlling, based on a result of the determining, notification of an alert indicating that the time-series data includes noise.

Abstract: In order to adequately suppress both an increase in NOx emission amount and deterioration of fuel consumption rate, the present invention provides a fuel injection control information generation device equipped with: a test point information storage unit for holding test point information including a plurality of test points constituted by sets of engine speed, fuel injection amount, and oxygen concentration; and a control information generation unit for generating, for each test point included in the test point information, fuel injection control information in which the engine speed, fuel injection amount, and oxygen concentration of the test point are associated with an optimum fuel injection timing at which an index pertaining to the total of a fuel consumption rate and an NOx emission amount in the test point becomes the smallest.

Abstract: An apparatus obtains time series data to which a label indicating a category of classification is attached, where the time series data contains variations of target values during a period to which the label is attached. The apparatus divides the time series data into a plurality of sections, and generates an attractor for each of the plurality of sections where the attractor indicates a set of numerical values toward which the variations of the target values tends to evolve. The apparatus calculates a Betti sequence in accordance with the generated attractor for each of the plurality of sections, and obtains a feature for the Betti sequences of the plurality of sections by clustering the Betti sequences or by calculating a statistical quantity of the Betti sequences. The apparatus performs machine learning by using the obtained feature as an input.

Abstract: A machine learning method includes: generating, by a computer, a sine wave using a basic period of input data having a periodic property; determining a sampling period based on a degree of roundness of an attractor generated from the sine wave; sampling the input data at the determined sampling period to generate a pseudo attractor; and performing a machine learning by using the pseudo attractor.

Abstract: In order to adequately suppress both an increase in NOx emission amount and deterioration of fuel consumption rate, the present invention provides a fuel injection control information generation device equipped with: a test point information storage unit for holding test point information including a plurality of test points constituted by sets of engine speed, fuel injection amount, and oxygen concentration; and a control information generation unit for generating, for each test point included in the test point information, fuel injection control information in which the engine speed, fuel injection amount, and oxygen concentration of the test point are associated with an optimum fuel injection timing at which an index pertaining to the total of a fuel consumption rate and an NOx emission amount in the test point becomes the smallest.

Abstract: A sensor output value estimation device that effectively estimates sensor output values reflecting a response delay of a temperature sensor. The device includes an estimated gas temperature calculation unit for calculating an estimated gas temperature of an engine on a basis of at least a running condition of the engine and a state quantity of the gas in the engine. The device also includes an estimated sensor output value calculation unit for calculating an estimated sensor output value reflecting the response delay of the temperature sensor on a basis of the calculated estimated gas temperature and a pre-stored first model formula specifying a relation among the temperature change time constant of the temperature sensor, the gas flow rate, and the gas temperature.

Abstract: An exhaust system state detection device includes an intake air oxygen concentration sensor that detects an oxygen concentration of an intake air of an engine, an engine revolution sensor and an accelerator position sensor that in combination detect a running condition, an indicated thermal efficiency calculation unit that calculates an amount of change in the indicated thermal efficiency of the engine based on the intake air oxygen concentration, the fuel injection start timing, and a first model formula defining the relation among the intake air oxygen concentration, the injection start timing, and the amount of change in the indicated thermal efficiency, and an exhaust gas temperature calculating unit that calculates an exhaust gas temperature based on the amount of change in the indicated thermal efficiency and a second model formula defining the relation between the exhaust gas temperature and the amount of change in the indicated thermal efficiency.

Abstract: A sensor output value estimation device that effectively estimates sensor output values reflecting a response delay of a temperature sensor. The device includes an estimated gas temperature calculation unit for calculating an estimated gas temperature of an engine on a basis of at least a running condition of the engine and a state quantity of the gas in the engine. The device also includes an estimated sensor output value calculation unit for calculating an estimated sensor output value reflecting the response delay of the temperature sensor on a basis of the calculated estimated gas temperature and a pre-stored first model formula specifying a relation among the temperature change time constant of the temperature sensor, the gas flow rate, and the gas temperature.

Abstract: According to one embodiment, a disk device rotates a disk information storage medium to record and reproduce information on the information storage medium by use of a head that slides in contact with a lubricant coated on the information storage medium, wherein a sliding speed U, area A and normal force N are set to cause U×A/N to fall within a monotonously increasing region in which a coefficient of friction associated with a frictional force occurring in a contact area of the head that faces the information storage medium monotonously increases as U×A/N increases, where the sliding speed U represents a sliding speed at a sliding time of the head, the area A represents the contact area of the head, and the normal force N represents a normal force applied to the contact area of the head.

Abstract: According to one embodiment, a disk device rotates a disk information storage medium to record and reproduce information on the information storage medium by use of a head that slides in contact with a lubricant coated on the information storage medium, wherein a sliding speed U, area A and normal force N are set to cause U×A/N to fall within a monotonously increasing region in which a coefficient of friction associated with a frictional force occurring in a contact area of the head that faces the information storage medium monotonously increases as U×A/N increases, where the sliding speed U represents a sliding speed at a sliding time of the head, the area A represents the contact area of the head, and the normal force N represents a normal force applied to the contact area of the head.

Abstract: According to one embodiment, a disk device rotates a disk information storage medium to record and reproduce information on the information storage medium by use of a head that slides in contact with a lubricant coated on the information storage medium, wherein a sliding speed U, area A and normal force N are set to cause U×A/N to fall within a monotonously increasing region in which a coefficient of friction associated with a frictional force occurring in a contact area of the head that faces the information storage medium monotonously increases as U×A/N increases, where the sliding speed U represents a sliding speed at a sliding time of the head, the area A represents the contact area of the head, and the normal force N represents a normal force applied to the contact area of the head.

Abstract: According to one embodiment, in a disk drive, a voice coil motor is controlled to cause a head to minutely vibrate in a radial direction on a track of a disk. When the voice coil motor vibrates the head in the radial direction of the disk, frictional force occurring between the disk and the head is calculated based on the driving force of the voice coil motor generated to vibrate and detected positional information, thereby measuring frictional characteristics.

Abstract: According to one embodiment, a disk device rotates a disk information storage medium to record and reproduce information on the information storage medium by use of a head that slides in contact with a lubricant coated on the information storage medium, wherein a sliding speed U, area A and normal force N are set to cause U×A/N to fall within a monotonously increasing region in which a coefficient of friction associated with a frictional force occurring in a contact area of the head that faces the information storage medium monotonously increases as U×A/N increases, where the sliding speed U represents a sliding speed at a sliding time of the head, the area A represents the contact area of the head, and the normal force N represents a normal force applied to the contact area of the head.