Abstract: A system converts a first input idea vector representing an idea into a first contracted vector. The system generates one or more second contracted vectors in a multivariate space to which the first contracted vector belongs, based on a value of a first predetermined component of the first contracted vector in the multivariate space. The system generates, respectively from the one or more second contracted vectors, one or more first output idea vectors representing a candidate idea to be proposed to a user. The multivariate space is configured to maintain a similarity between an input idea vector for generating a contracted vector and an output idea vector generated from the contracted vector and a similarity between the first predetermined component of the contracted vector and a first predetermined index value.

Abstract: Provided is a report writing support system including: a document model determination unit that determines a document model storing a template of a draft to be presented to a user, on the basis of an answer to a selective question and a question determination model that determines a further question to the answer; a template application unit that asks a descriptive question for asking a question about a content lacking in the template of the draft stored in the document model on the basis of the determined document model and the answer or a further answer, and applies an answer to the descriptive question to the template of the draft; and a presentation processing unit that presents the template of the draft, to which the answer to the descriptive question is applied, as a draft to be presented to the user.

Abstract: Provided is a moving body queue management system that can plan an estimated queue line of moving bodies in consideration of a main trajectory. Provided is the moving body queue management system that manages a queue of the moving bodies, the moving body queue management system including: an information management unit configured to manage moving information regarding movement of a moving body; and an estimated queue line planning unit configured to plan an estimated queue line for guiding the moving body to the queue based on the moving information such that at least a part of the queue of the moving bodies crosses a main trajectory.

Abstract: The draft document generating method repeats question processing for component elements selected from the case database to the user. The question processing presents, by an output device, one or more of the component elements selected from the case database to the user, presents a question as to whether the component elements are applicable to contents of a draft document to the user, acquires, via an input device, an answer of the user to the question; and adds the answer in an answer history. The selecting of the one or more component elements for which the question processing is to be executed next from unprocessed component elements in the plurality of cases is based on statistics of part of the component elements in the plurality of cases. The draft document is generated based on a component element indicating that the answer history is applicable to contents of the draft document.

Abstract: The measurement guide device is able to easily select the next measurement target on the basis of previously obtained measurement results. The measurement guide device includes a database, a similarity search section, and a next-point proposal section. The database stores a virtual measured signal and a measurement procedure that are obtained by simulation. The similarity search section extracts, from the database, virtual measured signals similar to measurement results obtained by a measurement device, and measurement procedures regarding the virtual measured signals. The next-point proposal section selects at least one measurement procedure from the measurement procedures obtained by the similarity search section, and determines the next measurement point.

Abstract: A simulation estimation model estimates a feature value of a simulation result of a material from a descriptor of the material. A material feature value estimation model estimates a feature value of the material from the estimation result of the simulation estimation model and the descriptor of the material. One or more processors input a descriptor of a first material into the simulation estimation model to acquire a first simulation estimation result of the feature value of the first material. The one or more processors input the first simulation estimation result and the descriptor of the first material into the material feature value estimation model to acquire the feature estimation value of the first material.

Abstract: A system for determining a material to propose to a user is disclosed. The system calculates an availability evaluation value indicating availability for a user of each of materials based on a chemical formula of each of the materials. The system estimates a physical property value of each of the materials based on a chemical formula of each of the materials. The system calculates a physical property evaluation value of each of the materials based on an estimation result of the physical property value of each of the materials. The system calculates an overlooking risk evaluation value indicating priority of presenting each of the materials to the user based on the availability evaluation value and the physical property evaluation value of each of the materials. The system selects a material to present as a candidate material from the materials according to the overlooking risk evaluation value.

Abstract: A structure model includes a first encoder that converts a compound structure representation to a real number vector and a first decoder that estimates the compound structure representation from the real number vector resulting from the conversion by the first encoder. A structure-property relationship model includes a second encoder that converts, to a real number vector, an extended vector including, as components, the real number vector generated by the first encoder and a target value vector including target values of one or more physical property values and a second decoder that estimates the extended vector from the real number vector generated by the second encoder.

Abstract: One or more storage devices store a first machine learning model and a second machine learning model. The one or more processors generate each low-dimensional descriptor including the predetermined number of elements for multiple materials, and predict each characteristic value of the multiple materials from the low-dimensional descriptor. One or more processors select a part of materials from multiple materials based on the characteristic value, and generate a high-dimensional descriptor having the number of elements larger than the predetermined number. One or more processors predict each characteristic value of the part of the materials from the high-dimensional descriptor using the second machine learning model.

Abstract: Provided is a report writing support system including: a document model determination unit that determines a document model storing a template of a draft to be presented to a user, on the basis of an answer to a selective question and a question determination model that determines a further question to the answer; a template application unit that asks a descriptive question for asking a question about a content lacking in the template of the draft stored in the document model on the basis of the determined document model and the answer or a further answer, and applies an answer to the descriptive question to the template of the draft; and a presentation processing unit that presents the template of the draft, to which the answer to the descriptive question is applied, as a draft to be presented to the user.

Abstract: The system includes a material property prediction presenting unit, a cross-task compatible feature value generating unit, and a material property predicting unit. The material property prediction presenting unit accepts a specification of first task data that includes a record in which a material property is unknown and is to be a target of material property prediction through a first predictive model. The cross-task compatible feature value generating unit predicts feature values from material compositions in the first task data by using a second predictive model. The material property predicting unit generates the first predictive model by using the material compositions, experimental condition, feature values, and the known material property in the first task data. Also, the material property predicting unit inputs the material composition, experimental condition, and feature value in a record in which the material property is unknown in the first task data and predicts the unknown material property.

Abstract: Effective compound feature quantities reflecting expert knowledge are efficiently generated to thereby accurately predict physical properties of an unknown compound with a device for predicting a material property using a case-by-case material database storing a plurality of case databases. The case databases include a plurality of records that record structural information about material structures in association with material properties about properties of materials. This device is includes a chemical space designation unit that receives a designation of at least one case database; an autoencoder learning unit that generates an autoencoder for converting structural information corresponding to the case database received by the chemical space designation unit to multi-variables; and a material property prediction unit that predicts material properties using the multi-variables converted by the autoencoder generated by the autoencoder learning unit.

Abstract: The present invention defines a spatial structure of a molecule without allowing freedom with respect to the selection of a coordinate system and predicts material properties based on a spatial structure of the molecule.

Abstract: Automated analysis of particle beam measurement results is facilitated by a device that calculates a spatial parameter distribution representing spatial structure of a sample based on a scattering pattern corresponding to projection of the spatial structure of the sample to wavenumber space, the projection being obtained by detecting scattering of a particle beam which enters the sample and intersects with the sample.

Abstract: A device control system includes a control request issuing unit for issuing a control request defining a position of a moving object and the device control according to operation of a user; a determination plan generation unit configured to, based on the control request, generating a condition; a determination unit for determining whether a condition of the control request related to the moving object is satisfied and issuing an identifier of the control request; at least one condition determination generated by the determination plan generation unit; an execution plan generation unit for generating a control execution unit configured to receive the identifier of the control request, identifying a device that is a control target according to a control rule defined in the control request, and transferring a control command according to a control procedure, and one or a plurality of control execution units generated by the execution plan generation unit.

Abstract: A movement route of a moving body within a predetermined area is simulated. A movement route prediction system 10 includes a flow line prediction model learning unit 105 that performs machine learning on a flow line prediction model which calculates a first objective variable from a first feature amount, and a movement route prediction unit 106 that simulates a route of a moving body based on the flow line prediction model. The flow line prediction model learning unit includes a flow line data division unit 1051 that divides information on a movement route into a plurality of divisions, and a machine learning unit 1053 that performs machine learning on the flow line prediction model for each piece of the divided information on the movement route of the moving body.

Abstract: The measurement guide device is able to easily select the next measurement target on the basis of previously obtained measurement results. The measurement guide device includes a database, a similarity search section, and a next-point proposal section. The database stores a virtual measured signal and a measurement procedure that are obtained by simulation. The similarity search section extracts, from the database, virtual measured signals similar to measurement results obtained by a measurement device, and measurement procedures regarding the virtual measured signals. The next-point proposal section selects at least one measurement procedure from the measurement procedures obtained by the similarity search section, and determines the next measurement point.

Abstract: On-site getting in and out data including the number of people who got in the elevator in the past is created, virtual getting in and out data including the number of people who get in the elevator is created by making people who arrive at a landing of the elevator virtually appear and simulating operation of the elevator on the basis of the number of people who appear, a first conversion model for converting the virtual getting in and out data before a certain time point into the number of people who appear after the certain time point and a second conversion model for converting the virtual getting in and out data after a certain time point into the number of people who appear before the certain time point are created on the basis of the number of people who appear and the virtual getting in and out data, a prediction model for predicting the number of people who appear after a certain time point from the number of people who appear before the certain time point is learned on the basis of the number of peop

Abstract: The multidimensional data management system for speedily registering and searching multidimensional data includes: a central processing unit and a storage device that stores the multidimensional data including the respective values of plural dimensions, and multidimensional management data associating the ranges of the respective values of plural dimensions with character strings.

Abstract: A device control system includes a control request issuing unit for issuing a control request defining a position of a moving object and the device control according to operation of a user; a determination plan generation unit configured to, based on the control request, generating a condition; a determination unit for determining whether a condition of the control request related to the moving object is satisfied and issuing an identifier of the control request; at least one condition determination generated by the determination plan generation unit; an execution plan generation unit for generating a control execution unit configured to receive the identifier of the control request, identifying a device that is a control target according to a control rule defined in the control request, and transferring a control command according to a control procedure, and one or a plurality of control execution units generated by the execution plan generation unit.