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公开(公告)号：US20230081583A1
公开(公告)日：2023-03-16
申请号：US17920052
申请日：2021-04-09
Applicant: Hitachi, Ltd.
Inventor： Takuya KANAZAWA , Hidekazu MORITA , Akinori ASAHARA , Takayuki HAYASHI
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.
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公开(公告)号：US20240403764A1
公开(公告)日：2024-12-05
申请号：US18699862
申请日：2022-10-04
Applicant: HITACHI, LTD.
Inventor： Hideya YOSHIUCHI , Hidekazu MORITA , Sayaka KURATA , Hiroki MIYAMOTO
IPC: G06Q10/0633 , G06Q10/0639
Abstract: A business information management server 1 includes: a performance data collection unit that collects performance data of each business process from a data generation device 4 for each business flow, and stores the collected performance data in a storage device in association with a business in the business process and related elements related to the business; and a performance data search unit that, when a business flow and a search condition regarding similarity of performance data are designated together with a reference business flow, extracts a business flow similar to the reference business flow from among a plurality of business flows associated with the performance data stored in the storage device on the basis of the search condition, extracts performance data similar to performance data of the reference business flow from among the performance data of the extracted business flow, and outputs an extraction result.
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公开(公告)号：US20230394227A1
公开(公告)日：2023-12-07
申请号：US18032283
申请日：2021-10-14
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Hidekazu MORITA , Takuya KANAZAWA
IPC: G06F40/166
CPC classification number: G06F40/166
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.
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公开(公告)号：US20230153491A1
公开(公告)日：2023-05-18
申请号：US17917009
申请日：2021-04-09
Applicant: Hitachi, Ltd.
Inventor： Takuya KANAZAWA , Akinori ASAHARA , Hidekazu MORITA
IPC: G06F30/27
CPC classification number: G06F30/27
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.
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公开(公告)号：US20230066125A1
公开(公告)日：2023-03-02
申请号：US17909007
申请日：2021-01-20
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Takuya KANAZAWA , Hidekazu MORITA
IPC: G06F40/186
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.
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Patent Agency Ranking
公开(公告)号：US20220359047A1
公开(公告)日：2022-11-10
申请号：US17621413
申请日：2020-08-19
Applicant: Hitachi, Ltd.
Inventor： Takuya KANAZAWA , Akinori ASAHARA , Takayuki HAYASHI , Hidekazu MORITA
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.
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公开(公告)号：US20220223234A1
公开(公告)日：2022-07-14
申请号：US17613099
申请日：2020-08-20
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Takayuki HAYASHI , Takuya KANAZAWA , Hidekazu MORITA
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. A material properties prediction system that predicts properties of a material includes a three-dimensional molecular structure calculation unit having a function of calculating positional coordinates of atoms constituting a molecule from a structural formula of the material; a spatial structure feature quantity calculation unit having a function of selecting three atoms to form a triangle based on the position coordinates of atoms calculated by the three-dimensional molecular structure calculation unit, and calculating, as a spatial structure feature quantity, distances between the three atoms and another atom; and a material properties prediction unit that predicts material properties using, as an explanatory variable, the spatial structure feature quantity generated by the spatial structure feature quantity calculation unit.
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公开(公告)号：US20250067688A1
公开(公告)日：2025-02-27
申请号：US18725869
申请日：2022-01-13
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Mitsuya YAMAMOTO , Hidekazu MORITA
Abstract: The particle beam analyzer includes: an uncertainty level evaluation unit that calculates an optimization target position constituting a spatial position specified on the basis of a variation in spatial density distribution for each spatial position with respect to a plurality of spatial density distributions corresponding to the profile selected by the profile selection unit; a differential regression analysis unit that calculates, using regression analysis, a function for obtaining, from the spatial density distribution, a difference from the input profile by using the data held in the profile database and the difference calculated by the profile difference evaluation unit; and a spatial density distribution optimization unit that calculates a spatial density distribution for which the difference of the function calculated by the differential regression analysis unit is minimized, by using, as a variable, only the spatial density in the optimization target position calculated by the uncertainty level evaluation unit.
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公开(公告)号：US20230143768A1
公开(公告)日：2023-05-11
申请号：US17918581
申请日：2021-04-09
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Hidekazu MORITA , Takayuki HAYASHI , Takuya KANAZAWA , Yoshihiro OSAKABE
IPC: G06Q30/0601 , G06Q30/02
CPC classification number: G06Q30/0631 , G06Q30/0278
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.
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公开(公告)号：US20220358438A1
公开(公告)日：2022-11-10
申请号：US17621321
申请日：2020-08-19
Applicant: Hitachi, Ltd.
Inventor： Akinori ASAHARA , Takayuki HAYASHI , Takuya KANAZAWA , Hidekazu MORITA
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.
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