Hitachi, Ltd.

Hitachi High-Tech Corporation

Yasuhide Mori

Masashi Egi

Masahiro Kato

Minako Toba

Naofumi Hama

Norifumi Nishikawa

Hiroshi Tsuji

Takao Sakurai

Kenichi Yoshida

Takeshi Ohmori

Tomohiro Nakamura

Tsuyoshi Minakawa

Ken Naono

Yoshio Miki

Katsuro Kikuchi

Hiromitsu Nakagawa

Nobuhiro Sekimoto

Yuko Yamashita

Masayoshi Mase

Kohei Matsuda

Yuxin Liang

Yuichi Kobayashi

Kazumasa Tokuhashi

Satoshi Sakai

Hirotake Yoshida

Hiroyuki Namba

Naoaki Yokoi

Yumiko Ishido

Takafumi Hosokawa

Yuyao Wang

Atsushi Toyama

An operation plan change assistance system includes a determination model generation unit configured to generate an operation plan change determination model that receives information about a train operation content before a certain point in time and information about a change in an operation plan executed before the point in time and outputs information about a change in operation plan to be executed next; and an operation plan change proposal creation unit configured to input information about a train operation content before a point in time designated by a user and information about a change in an operation plan executed before the designated point in time, create change candidates that are candidates for each change in an operation plan to be executed in stages after the designated point in time, specify a change candidate that satisfies a predetermined condition, and create the specified change candidate as an operation plan change proposal.

Operation plan change assistance device, operation plan change assistance method, and rail traffic management system

For a machine learning model that receives control parameters of a semiconductor processing device and outputs shape parameters that express a processed shape of a semiconductor sample processed by the semiconductor processing device, an experiment point obtaining learning data is recommended. A contribution of each control parameter to the prediction of the machine learning model is evaluated from feature quantity data that is a value of a control parameter of the learning data used for learning of the machine learning model, and the experiment point is recommended based on a stability evaluation and an uncertainty evaluation of the prediction by the machine learning model in a space defined by the control parameters selected based on the contribution as axes.

Experiment point recommendation device, experiment point recommendation method, and semiconductor device manufacturing device

There is provided is a computer system that outputs a predicted value of data to be evaluated using a predictor generated using learning data. The computer system includes the predictor; an index calculation unit that calculates an interpretation index of the data to be evaluated; and an extraction unit that selects the learning data useful for a user to interpret the predicted value of the data to be evaluated, wherein index management information for managing an interpretation index of the learning data is stored, the index calculation unit calculates the interpretation index of the data to be evaluated, and the extraction unit calculates a selection index based on the interpretation index of the data to be evaluated and the interpretation index of the learning data, selects the learning data based on the selection index, and outputs display information for presenting information indicating a processing result.

Computer system and method of presenting information related to basis of predicted value output by predictor

A computer system stores interpretation factor conversion information for managing an interpretation factor interpreting a basis of a prediction result for input data, the interpretation factor is determined by a value of each of a plurality of feature quantities contained in the input data including values of the plurality of feature quantities, and a first evaluation value of each of the plurality of feature quantities contained in the input data. When evaluation target data is input, the computer system calculates a prediction result, calculates a contribution value of each of the plurality feature quantities contained in the evaluation target data, specifies a corresponding interpretation factor, based on a value and a contribution value of each of the plurality of feature quantities contained in the evaluation target data, by referring to the interpretation factor conversion information, and generates and outputs display information for presenting the specified interpretation factor.

Computer system and method of presenting information on basis of prediction result for input data

A computer system includes a processor for executing a program, a computer holding the program executed by the processor, a first database holding relevance between physical amounts measured under conditions different in at least one of time and place, and a second database holding relevance between pieces of information including texts and corresponding to the measured physical amounts. The processor is configured to: calculate, based on the relevance between the physical amounts held in the first database and the relevance between the pieces of information in the second database, relevance between each of the measured physical amounts and each of the pieces of information, and hold the calculated relevance between each of the physical amounts and each of the pieces of information in a third database; and refer to, when the physical amounts are input, the third database to present information highly relevant to the input physical amounts.

Computer system and information presentation method using computer system

Provided is an information recommendation system capable of recommending an unexpected item which a user is interested in but cannot assume easily. A server gives one or more times of initial recommendations of recommending information by a means of a user profile and a behavior history, and narrows down second recommended items to recommend next by using not only information relating to items having responses but also information relating to items having no response together. In narrowing down, the items are arranged by means of an item arrangement program by using the results of the initial recommendations, and it is identified depending on similarity by means of a boundary calculation program where the boundary between user's interest and no interest is positioned in all the items. Then, it is identified where items not recommended yet are positioned in user's interest/no interest the areas, and items in the vicinity of the boundary between the interest and no interest are determined as the second recommended items which are not uninterested and maximize unexpectedness.

Method of recommending information, system thereof, and server

Model data is generated from performance information sorted by day of the week, time period, and process status by a performance information analysis section and a process status analysis section. An abnormality determination section detects abnormality using appropriate model data. What the graph of an expected status is like, how much the graph of the current status that has been determined abnormal differs from the graph of the expected status, and how much the current status is like the expected status are displayed allowing a system manager to observe detailed information about abnormality determination.

Abnormality detection method, device and program

An environmental control system according to the present invention is a system for controlling environmental devices by which a work status and a behavior status are monitored and the environmental devices are finely controlled in accordance with the statuses to improve comfort. The environmental control system includes a communication unit, a unit for detecting environments, a unit for detecting a work status, a unit for obtaining power consumption, a unit for determining the control of a device, and a unit for transmitting a control signal, and enables fine control in accordance with a work type.

Intra-area environmental control system and intra-area environmental control method

A home system for supporting a life behavior, in which a user can effectively select a function or content quickly according to attributes and states of display devices arranged in respective locations and the user behavior. A storage unit holds location attribute information on the devices, time band dependent use frequency for each user, and location dependence of each. A user identifier input unit identifies a user using a function or content. When displaying a menu for the user to select a content and a function, a calculation unit references each database of the storage unit in accordance with the menu display state and generates menu content information correlated to the content and the function. A display unit displays such a menu that the user can easily select a content and a function with higher priority rank according to the menu content information.

Method for user interface, display device, and user interface system

With respect to a data transfer over a network, data is stored in each cache of the network and the retrieving processing following the second retrieving processing is executed by using a cache, thereby resulting in a transfer amount being decreased. Statistics information of a data transfer over the network is obtained. When transfer data is stored in a low-speed storage such as a disk, only data of high access frequency is stored and data of low access frequency is discarded, thereby solving such a problem that a speed of a disk apparatus becomes a bottleneck.

Caching managing method for network and terminal for data retrieving

Growing community of inventors

Kawasaki, Japan

Yasuhide Mori