Abstract: Provided is a method of producing a feed or food product in which an inner layer is encrusted with a gelled outer layer composition, the method including the steps of: preparing an outer layer composition feedstock by adding a secondary feedstock to a protein feedstock and/or a starch feedstock that forms a gel upon heating and then mixing by stirring, and preparing an inner layer composition that is encrusted with the outer layer composition; extrusion molding with an extruder provided with a double nozzle so as to cover a surface of the inner layer composition while simultaneously gelling the outer layer composition feedstock by heat treatment; and cutting a continuously extruded cylindrically shaped product to a fixed length with a shutter mechanism while simultaneously encrusting a cut surface with the gelled outer layer composition.

Abstract: In a noise removing apparatus, a data acquisition unit acquires sets of odor data measured using a sensor with respect to a plurality of objects, each set of odor data representing features of an odor of an object by respective rates of a plurality of odor molecules. A noise component extraction unit extract a noise component using a set of odor data. A noise removing unit removes the noise component from each set of odor data to be processed.

Abstract: An information processing device is configured to include an acquisition unit, a determination unit, an instruction unit, an instruction unit, and output unit. The acquisition unit is configured to acquire measurement target and measurement environment information, and measurement environment information that a measurer can measure with an odor sensor. The determination unit is configured to determine a measurement target that the measurer should be instructed to measure, based on the measurement target and measurement environment information and the measurement environment information that can be measured, the instruction is configured to instruct the measurer to measure the determined measurement target. The output unit configured to output a reward to the measurer after the acquisition means acquires odor data of the determined measurement target.

Abstract: In a data generation apparatus, an acquisition unit acquires original data which are odor data measured in a specific environment. A generation unit performs a linear transformation with respect to the original data, and generates augmented data which are odor data in an environment where temperature and humidity are different from those in the specific environment.

Abstract: In a noise removing apparatus, a data acquisition unit acquires sets of odor data measured using a sensor with respect to a plurality of objects, each set of odor data representing features of an odor of an object by respective rates of a plurality of odor molecules. A noise component extraction unit extract a noise component using a set of odor data. A noise removing unit removes the noise component from each set of odor data to be processed.

Abstract: A training data generation device includes a label candidate generation unit, a reception unit, and a training data generation uni. The acquisition unit is configured to acquire smell data and information pertaining to the smell data. The label candidate generation unit which generates label candidates on the basis of the information pertaining to the smell data; an output unit which outputs the generated label candidates. The reception unit is configured to receive selection of a label from the output label candidates. The training data generation unit which generates training data from the selected label and the smell data.

Abstract: An information processing apparatus (2000) acquires a feature vector (20) obtained based on signal data (14) of a detected value of a sensor (10) that senses gas to be measured. The information processing apparatus (2000) decomposes the feature vector (20) into a product of a coefficient vector and a feature matrix by using a non-negative matrix factorization (NMF). The detected value of the sensor (10) changes according to an attachment and a detachment of a molecule contained in a sensed gas. A value of each element of the feature vector (20) is equal to or greater than zero.

Abstract: A learning apparatus acquires learning data in which odor data of each object and a label representing the object in a label space expressing features of odors are associated with each other, and learns, based on odor data, a model for predicting a label of the odor data in the label space, by using the learning data. In a data processing apparatus for processing odor data, an acquisition unit acquires odor data from an outside. A prediction unit predicts a label of the acquired odor data in the label space by using the model in which a relationship between sets of odor data and labels in the label space expressing the features of the odors is learned.

Abstract: To mitigate degradation in the accuracy of a prediction model by re-learning the prediction model with consideration given to the characteristics of a detection value of a sensor. This prediction model re-learning device comprises: a calculation unit that, on the basis of data related to smell detection by a sensor, calculates an index for determining whether or not to re-learn a prediction model for smell; and a re-learning unit that re-learns the prediction model in cases where the calculated index satisfies a predetermined condition.

Abstract: A control apparatus (10) includes a signal detection unit (110) and a data acquisition unit (120). The signal detection unit (110) acquires operation signals relating to an operation of a processing apparatus (20) that processes food and drink, and detects a specific operation signal relating to a specific operation from among the operation signals. The data acquisition unit (120) determines, based on a detection timing of the specific operation signal, a data acquisition period of an odor sensor (30) provided in the processing apparatus (20), and acquires output data being output from the odor sensor (20) during the data acquisition period.

Abstract: An information processing apparatus (2000) acquires a feature vector (20) obtained based on signal data (14) of a detected value of a sensor (10) that senses gas to be measured. The information processing apparatus (2000) decomposes the feature vector (20) into a product of a coefficient vector and a feature matrix by using a non-negative matrix factorization (NMF). The detected value of the sensor (10) changes according to an attachment and a detachment of a molecule contained in a sensed gas. A value of each element of the feature vector (20) is equal to or greater than zero.

Abstract: A display control apparatus includes an operation detector detecting an operation indicating a movement direction, an object analysis device specifying an object to which a focus is moved by a one-time operation among objects displayed on a screen and operated by a user, as an object of a first group, and a display properties setting device setting display properties of the object of the first group so that the user may distinguish the object of the first group from other objects.