Patents by Inventor Takeshi OSOEKAWA

Takeshi OSOEKAWA has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20200292509
    Abstract: When chromatogram data for a target sample have been acquired, a peak position estimator determines an estimated result of the position of the starting and/or ending point of a peak as well as the confidence value representing the reliability of the estimation, using a trained model stored in the trained model storage section. Normally, a plurality of estimated results of the starting point and/or ending point of the peak are acquired for one peak. A peak information correction processor identifies a candidate having the highest confidence as a prime candidate, and superposes a plurality of candidates including the prime candidate, with their respective confidence values, on a displayed chromatogram. An operator referring to the confidence values selects a peak which needs close checking or correction, and corrects the starting point and/or ending point of the selected peak, for example, by selecting and indicating a candidate other than the prime candidate.
    Type: Application
    Filed: November 9, 2017
    Publication date: September 17, 2020
    Applicant: SHIMADZU CORPORATION
    Inventors: Takeshi OSOEKAWA, Yusuke HIDA, Yuzi KANAZAWA, Shinji KANAZAWA, Yohei YAMADA, Hiroyuki YASUDA, Akihiro KUNISAWA
  • Publication number: 20200279408
    Abstract: A model constructed by a training process using the technique of deep learning using the training data including images created from a large number of chromatograms and correct peak information is previously stored in a trained model storage section. When chromatogram data for a target sample acquired with an LC measurement unit are inputted, an image creator converts the chromatogram into an image and creates an input image in which one of the two areas divided by the chromatogram curve as the boundary in the image is filled. A peak position estimator inputs the pixel values of the input image into a trained model using a neural network, and obtains the position information of the starting point and/or ending point of the peak and a peak detection confidence as the output. A peak determiner determines the starting point and/or ending point of each peak based on the peak detection confidence.
    Type: Application
    Filed: November 9, 2017
    Publication date: September 3, 2020
    Applicant: SHIMADZU CORPORATION
    Inventors: Takeshi OSOEKAWA, Yusuke HIDA, Yuzi KANAZAWA, Shinji KANAZAWA, Yohei YAMADA, Hiroyuki YASUDA, Akihiro KUNISAWA, Hidetoshi TERADA
  • Publication number: 20200234140
    Abstract: A learning method executed by a computer, the learning method includes: learning parameters of a machine learning model having intermediate feature values by inputting a plurality of augmented training data, which is generated by augmenting original training data, to the machine learning model so that specific intermediate feature values, which are calculated from specific augmented training data augmented from a same original training data, become similar to each other.
    Type: Application
    Filed: January 14, 2020
    Publication date: July 23, 2020
    Applicant: FUJITSU LIMITED
    Inventors: TAKASHI KATOH, Kento UEMURA, Suguru YASUTOMI, Takeshi OSOEKAWA
  • Publication number: 20200193329
    Abstract: A computer-implemented learning method includes inputting a plurality of pieces of input data and labels representing the plurality of pieces of input data into an encoder configured to output context variables associated with each of the plurality of pieces of input data, inputting the plurality of pieces of input data and the context variables output by the encoder into a decoder configured to output decision labels associated with the plurality of pieces of input data respectively, and learning parameters of the encoder and the decoder so that each of the decision labels matches with a corresponding label of the labels representing the plurality of the plurality of pieces of input data.
    Type: Application
    Filed: December 13, 2019
    Publication date: June 18, 2020
    Applicant: FUJITSU LIMITED
    Inventors: Takeshi OSOEKAWA, TAKASHI KATOH, Yusuke Hida, Yuzi KANAZAWA
  • Patent number: 9646265
    Abstract: A model updating method is provided. The model updating method that is executed by a computer includes calculating a score that indicates a degree of normality or abnormality of each of a plurality of pieces of data by using as a judgment model each of the pieces of data, predicting as a predicted condition whether each of the pieces of data is normal or abnormal according to score, judging whether or not the predicted condition is correct for each of the plurality of pieces of data, calculating the accuracy rate for the predicted conditions of a top specified number of pieces of data in order of decreasing abnormality as indicated by the score when the plurality of pieces of data are arranged in a specified order of score, and judging whether or not it is necessary to update the judgment model according to the accuracy rate.
    Type: Grant
    Filed: September 10, 2015
    Date of Patent: May 9, 2017
    Assignee: FUJITSU LIMITED
    Inventors: Takahisa Ando, Takeshi Osoekawa, Seishi Okamoto
  • Publication number: 20170032331
    Abstract: A clip detects that the physical link with an object, such as a document, is generated and/or the physical link with an object is eliminated. When the clip detects that the link with an object is generated, the clip transmits an identifier of the clip. Alternatively, when the clip detects that the link with an object is eliminated, the clip transmits an identifier of the clip.
    Type: Application
    Filed: June 23, 2016
    Publication date: February 2, 2017
    Inventors: Kazuki Takano, Motoshi Sumioka, Takeshi Osoekawa, Takuya Sakamoto, Daichi Shimada, Ayuri Morimoto, Tazuru Tanamori
  • Publication number: 20160307222
    Abstract: An information processing method includes: dividing processing target data, which indicates an action detected for each of a plurality of persons in a certain period, by a predetermined period length with reference to information related to a time contained in the data and separately performing a principal component analysis in each of the divided period length, by a processor; specifying corresponding axes in temporally adjacent analysis periods based on an axis calculated as a result of each principal component analysis, by the processor; and considering axes associated in the temporally adjacent periods as the same axis throughout all of the processing target data, and grouping the plurality of persons into a plurality of groups, by the processor.
    Type: Application
    Filed: June 20, 2016
    Publication date: October 20, 2016
    Applicant: FUJITSU LIMITED
    Inventors: Takeshi OSOEKAWA, Junichi Hirose, Takahisa Ando, Seishi OKAMOTO
  • Publication number: 20160063186
    Abstract: A server device displays a graph indicating time-series variation in load calculated according to a category of an event acquired from schedule information in which events of at least one user have been registered, and displays information indicating a payment object or a body region or symptom related to the payment object extracted from registered payment data of the one user in a manner temporally associated with the graph.
    Type: Application
    Filed: August 13, 2015
    Publication date: March 3, 2016
    Inventors: Shiho Miyatake, Takeshi Osoekawa, Junya Fujimoto
  • Publication number: 20150379432
    Abstract: A model updating method is provided. The model updating method that is executed by a computer includes calculating a score that indicates a degree of normality or abnormality of each of a plurality of pieces of data by using as a judgment model each of the pieces of data, predicting as a predicted condition whether each of the pieces of data is normal or abnormal according to score, judging whether or not the predicted condition is correct for each of the plurality of pieces of data, calculating the accuracy rate for the predicted conditions of a top specified number of pieces of data in order of decreasing abnormality as indicated by the score when the plurality of pieces of data are arranged in a specified order of score, and judging whether or not it is necessary to update the judgment model according to the accuracy rate.
    Type: Application
    Filed: September 10, 2015
    Publication date: December 31, 2015
    Inventors: Takahisa Ando, Takeshi OSOEKAWA, Seishi OKAMOTO
  • Publication number: 20140297690
    Abstract: A disclosed method includes: obtaining, for each node of plural nodes in a graph, which are associated each other, a display position at which the node is displayed; calculating, for each node, a movement vector according to a total sum of forces in conformity with a mechanics model in which an inertial force does not work, wherein the total sum of the forces is obtained by adding, with respect to all of nodes other than the node, a force that works in association with a distance concerning the display position with another node; moving, for each node, the display position by the calculated movement vector; and while repeating or before the obtaining, the calculating and the moving, accepting an instruction corresponding to a user's operation for causing a display position of a certain node to be changed, and changing the display position of the certain node according to the instruction.
    Type: Application
    Filed: February 7, 2014
    Publication date: October 2, 2014
    Applicant: FUJITSU LIMITED
    Inventors: Takeshi OSOEKAWA, Takahisa ANDO, Seishi OKAMOTO