Abstract: An indicator related to work performed through a plurality of hierarchical processes is predicted efficiently with high accuracy. The information processing device stores sample data in association with each parameter representing work, the sample data including an indicator generated by execution of lower-level simulation based on a lower-level model set for a lower-level process, and the information processing device predicts an indicator related to predicted work by performing higher-level simulation using the sample data associated with a parameter similar to a parameter representing the predicted work, the higher-level simulation being based on a higher-level model which is set for a higher-level process. If sample data associated with a parameter similar to the parameter representing the predicted work is not stored, the information processing device complements sample data by performing lower-level simulation and performs higher-level simulation using the complemented sample data.

Abstract: A plurality of workpieces include a plurality of first workpieces of a first workpiece group to be loaded onto a first loaded member according to a first loading sequence and a plurality of second workpieces of a second workpiece group to be loaded onto a second loaded member according to a second loading sequence. On a conveying device, workpieces are arranged at ransom with respect to respective arrangement sequences of the first workpiece group and the second workpiece group and the classifications of the first workpiece group and the second workpiece group. On a conveying device, workpieces of the first workpiece group are sequentially arranged based on the first loading sequence and workpieces of the second workpiece group are sequentially arranged based on the second loading sequence. At the same time, the workpieces of the first workpiece group and the second workpiece group are arranged together.

Abstract: A technology that can enhance the computing performance of a computing system using reservoir computing (RC), includes a computing system which performs computation using a recurrent neural network (RNN) including an input unit, a reservoir unit, and an output unit. The reservoir unit includes a plurality of nodes circularly connected to each other. The circular connection has a weight matrix for determining a weight between the nodes of the plurality of nodes, in which a weight between the nodes closely arranged on the circle is larger than a weight between the nodes arranged away from each other on the circle. The plurality of nodes each have a g value that is a parameter for designating nonlinearity of an activation function of each of the nodes, and that is set so as to periodically change in a direction on the circle.

Abstract: A device includes an input unit, a nonlinear converter, and an output unit. The nonlinear converter and the output unit are connected via a connection path having a delay mechanism that realizes a feedback loop giving a delay to a signal. The delay mechanism includes a conversion mechanism that generates a plurality of signals with different delay times using the signal output from the nonlinear converter, generates a new signal by superimposing the plurality of signals, and outputs the generated signal to the output unit.

Abstract: Provided is a computer system for generating a neural network (NN) used for a task including a training unit that calculates a weighting factor between a reservoir and an output layer using training data, a first storage unit that stores, as node activity information, information on a node activity level of a node included in the reservoir, and a second storage unit that stores model information. When receiving a training execution request for a second task after a training process of a first task is completed, the training unit calculates a weighting factor of the NN used for a third task obtained by combining the first task and the second task, updates the model information based on the calculated weighting factor, and updates the node activity information based on the node activity measured during execution of the training process of the third task.

Abstract: A technology that can enhance the computing performance of a computing system using reservoir computing (RC), includes a computing system which performs computation using a recurrent neural network (RNN) including an input unit, a reservoir unit, and an output unit. The reservoir unit includes a plurality of nodes circularly connected to each other. The circular connection has a weight matrix for determining a weight between the nodes of the plurality of nodes, in which a weight between the nodes closely arranged on the circle is larger than a weight between the nodes arranged away from each other on the circle. The plurality of nodes each have a g value that is a parameter for designating nonlinearity of an activation function of each of the nodes, and that is set so as to periodically change in a direction on the circle.

Abstract: A computer includes a data generation unit and a storage unit which retains graph information for managing a graph configured from a plurality of vertexes and sides. The data generation unit performs acquiring a plurality of data and graph information and assuring storage regions in number equal to the number of vertexes, converting each data into an input value and setting at least one input value to a storage region corresponding to at least one vertex, executing an updating process for updating a value set to a storage region corresponding to a first vertex using the value set to the storage region corresponding to the first vertex and a value set to a storage region corresponding to a different vertex directly connected to the first vertex, and outputting a set of values set to the storage regions corresponding to the vertexes as the feature value.

Abstract: To provide a sample for measuring particles enabling the three-dimensional particulate shape to be measured and the particulate species to be evaluated, the sample for measuring particles includes a substrate; isolated nanoparticles to be measured which are disposed on the substrate; and isolated standard nanoparticles which are disposed on the substrate in the vicinity of the isolated nanoparticles to be measured.

Abstract: An artificial olfactory sensing system includes a sensor unit. The sensor unit includes a semiconductor device equipped with a transistor and a sensor cell in which an olfactory receptor is manifested on a lipid film. A proton adsorption film is formed on a gate electrode of the transistor. A physiological aqueous solution is disposed on the proton adsorption film. Then, the sensor cell is disposed in the physiological aqueous solution. A proton is adsorbed onto the proton adsorption film. When the olfactory receptor recognizes an odor molecule, the positive ions in the physiological aqueous solution flow from an ion channel of the olfactory receptor into the sensor cell. As a result, the proton is dissociated from the proton adsorption film into the physiological aqueous solution, and the potential of the gate electrode is changed.

Abstract: An object of the present invention is to provide an artificial olfactory sensing system capable of sniffing out various odors highly sensitively. The artificial olfactory sensing system includes: plural sensor cells on a lipid membrane of each of which olfactory receptors have developed; and plural ion-sensitive field-effect transistors (ISFETs) that correspondingly exist to the sensor cells on a one-on-one basis. A response signal showing that each of the olfactory receptors of each of the sensor cells has recognized an odor molecule is converted into an electric signal by an ISFET corresponding to each of the sensor cells.

Abstract: To provide a sample for measuring particles enabling the three-dimensional particulate shape to be measured and the particulate species to be evaluated, the sample for measuring particles includes a substrate; isolated nanoparticles to be measured which are disposed on the substrate; and isolated standard nanoparticles which are disposed on the substrate in the vicinity of the isolated nanoparticles to be measured.

Abstract: A device includes an input unit, a nonlinear converter, and an output unit. The nonlinear converter and the output unit are connected via a connection path having a delay mechanism that realizes a feedback loop giving a delay to a signal. The delay mechanism includes a conversion mechanism that generates a plurality of signals with different delay times using the signal output from the nonlinear converter, generates a new signal by superimposing the plurality of signals, and outputs the generated signal to the output unit.

Abstract: A computer system that executes computation processing using a recurrent neural network constituted with an input unit, a reservoir unit, and an output unit. The input unit includes an input node that receives a plurality of time-series data, the reservoir unit includes a nonlinear node accompanying time delay, the output unit includes an output node calculating an output value. The input unit calculates a plurality of input streams by executing sample and hold processing and mask processing on a plurality of received time-series data, executes time shift processing that gives deviation in time to each of the plurality of input streams and superimposes the plurality of input streams subjected to the time shift processing, thereby calculating input data.

Abstract: An object of the present invention is to provide an artificial olfactory sensing system capable of sniffing out various odors highly sensitively. The artificial olfactory sensing system includes: plural sensor cells on a lipid membrane of each of which olfactory receptors have developed; and plural ion-sensitive field-effect transistors (ISFETs) that correspondingly exist to the sensor cells on a one-on-one basis. A response signal showing that each of the olfactory receptors of each of the sensor cells has recognized an odor molecule is converted into an electric signal by an ISFET corresponding to each of the sensor cells.

Abstract: This sample holder for a scanning probe microscope is constituted of (1) a container that retains a liquid and (2) a flat-plate-shaped upper cover that covers an upper opening of the container and that has a narrow slit above the position where a sample is placed. In the upper cover, the slit has a slit width with which a thin film of the liquid is formed over the upper surface of the sample when the liquid fills the space between the container and the upper cover. The thin film of the liquid has a film thickness smaller than the distance between the upper surface of the sample and the upper cover.

Abstract: There is a provided a chemical sensor that includes a semiconductor substrate of a first conductivity type, a first electrode that is formed on a front surface of the semiconductor substrate, a second electrode that is disposed to face the first electrode in a vertical direction, a flow path in which a liquid or a gas can flow between the first electrode and the second electrode, and a chemical substance capturing portion that is disposed in at least a partial region between the first electrode and the second electrode in the flow path, and bonded with a predetermined chemical substance, and in which a distance between the first electrode and the second electrode is set to be 2 nm or more and 200 nm or less, and a change in dielectric constant between the first electrode and the second electrode is detected.

Abstract: A computer includes a data generation unit and a storage unit which retains graph information for managing a graph configured from a plurality of vertexes and sides. The data generation unit performs acquiring a plurality of data and graph information and assuring storage regions in number equal to the number of vertexes, converting each data into an input value and setting at least one input value to a storage region corresponding to at least one vertex, executing an updating process for updating a value set to a storage region corresponding to a first vertex using the value set to the storage region corresponding to the first vertex and a value set to a storage region corresponding to a different vertex directly connected to the first vertex, and outputting a set of values set to the storage regions corresponding to the vertexes as the feature value.

Abstract: This sample holder for a scanning probe microscope is constituted of (1) a container that retains a liquid and (2) a flat-plate-shaped upper cover that covers an upper opening of the container and that has a narrow slit above the position where a sample is placed. In the upper cover, the slit has a slit width with which a thin film of the liquid is formed over the upper surface of the sample when the liquid fills the space between the container and the upper cover. The thin film of the liquid has a film thickness smaller than the distance between the upper surface of the sample and the upper cover.