Patents by Inventor Takeshi Kurashima

Takeshi Kurashima 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: 20250045630
    Abstract: A construction method of a trained model includes six processes. In a first process, data for performing machine learning of an operation of a controlled machine by a human is collected. In a second process, collected data that is the data collected is evaluated and, when it does not satisfy a predetermined evaluation criterion, the data is collected again. In a third process, training data is selected from the collected data that satisfies the evaluation criterion. In a fourth process, the training data is evaluated and, when it does not satisfy a predetermined evaluation criterion, the training data is selected again. In a fifth process, a trained model is constructed by machine learning using the training data that satisfies the evaluation criterion. In a sixth process, the trained model is evaluated and, when it does not satisfy a predetermined evaluation criterion, the trained model is trained again.
    Type: Application
    Filed: September 5, 2022
    Publication date: February 6, 2025
    Applicant: KAWASAKI JUKOGYO KABUSHIKI KAISHA
    Inventors: Hitoshi HASUNUMA, Takeshi YAMAMOTO, Kazuki KURASHIMA, Ayumi KISHIDA, Masayuki KAMON
  • Patent number: 12198402
    Abstract: A hazard estimation unit 21 estimates a likelihood of an occurrence of an event according to a hazard function, with respect to each of a plurality of pieces of time-series data that are a series of multiple pieces of data to which an event occurrence time relevant to the data is given in advance and that include time-series data in which the event did not occur and time-series data in which the event occurred. A parameter estimation unit 22 estimates a parameter of the hazard function so as to optimize a likelihood function expressed by including the event occurrence time given with respect to each of the plurality of pieces of time-series data and the likelihood of the occurrence of the event estimated with respect to each of the plurality of pieces of time-series data.
    Type: Grant
    Filed: May 22, 2019
    Date of Patent: January 14, 2025
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yoshiaki Takimoto, Yusuke Tanaka, Takeshi Kurashima, Shuhei Yamamoto, Maya Okawa, Hiroyuki Toda
  • Publication number: 20240386319
    Abstract: Provided is a prediction apparatus including a feature extraction unit configured to extract a feature based on past behavior series data of a prediction target and output behavior feature data, a behavior series prediction unit configured to predict a future behavior series of the prediction target based on the behavior feature data using a trained behavior series prediction model for predicting a behavior series, and a mood series prediction unit configured to predict a future mood series of the prediction target based on the behavior feature data and past mood series data of the prediction target using a trained mood series prediction model for predicting a mood series.
    Type: Application
    Filed: May 28, 2021
    Publication date: November 21, 2024
    Inventors: Shuhei YAMAMOTO, Takeshi KURASHIMA, Hiroyuki TODA, Tomu TOMINAGA
  • Patent number: 12146752
    Abstract: An intersection determination is made regarding whether or not a traffic route included in map information intersects a boundary between areas on a basis of the traffic route and an area shape between areas that are adjacent in the map information, the intersection determination being made for each pair of adjacent areas. On a basis of a weight determined for the boundary in a case where the intersection determination is made that no intersection exists, a movement cost graph expressing a movement cost for each area that accounts for the weight is constructed. A corrected shortest distance between areas is calculated on a basis of the movement cost graph. A human mobility between areas is estimated for each timestep, the timestep being the length of a predetermined time interval, according to a predetermined function for estimating the human mobility between areas on a basis of the corrected shortest distance between areas and a population of each of the areas at different predetermined times.
    Type: Grant
    Filed: May 27, 2019
    Date of Patent: November 19, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yasunori Akagi, Takuya Nishimura, Takeshi Kurashima, Hiroyuki Toda
  • Publication number: 20240379023
    Abstract: An information processing apparatus includes a data acquisition unit that acquires data indicating a relationship between success or failure of a task and an amount of a loss-framed incentive indicating an incentive that is forfeited in a case where the task is not successful, and information indicating a motivation function representing motivation of a user for the task, a parameter determination unit that determines a parameter of the motivation function based on the data, and an incentive measure calculation unit that calculates an incentive measure indicating an amount of a loss-framed incentive based on the determined parameter and the motivation function.
    Type: Application
    Filed: September 17, 2021
    Publication date: November 14, 2024
    Inventors: Yuka NISHIDA, Hideaki KIN, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20240345690
    Abstract: Disclosed herein is a touch panel including: a sensor substrate and a cover substrate stuck to each other. The sensor substrate includes a sensor electrode, and plural signal wirings electrically connected to the sensor electrode and extending along a periphery of the sensor electrode. The cover substrate includes one or plural conductive layers extending along the periphery of the sensor electrode and the plural signal wirings within an area not facing the sensor electrode and the plural signal wirings.
    Type: Application
    Filed: June 27, 2024
    Publication date: October 17, 2024
    Inventors: Takeshi KURASHIMA, Shoji HINATA
  • Patent number: 12056634
    Abstract: The present disclosure enables vehicle dispatch in consideration of individual differences of each orderer for a price and a required time by a computer executing an input procedure to input parameters for a distance matrix relating to a distance between a taxi and an orderer giving a taxi dispatch order, a travel distance for an order, an opportunity cost parameter for a taxi driver, and an acceptance probability function of the orderer, and a calculation procedure to calculate a price and a required time to be presented to the orderer by solving an optimization problem formulated using the parameters.
    Type: Grant
    Filed: November 19, 2019
    Date of Patent: August 6, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yuya Hikima, Masahiro Kojima, Yasunori Akagi, Tatsushi Matsubayashi, Takeshi Kurashima, Hiroyuki Toda
  • Patent number: 12050753
    Abstract: Disclosed herein is a touch panel including: a sensor substrate and a cover substrate stuck to each other. The sensor substrate includes a sensor electrode, and plural signal wirings electrically connected to the sensor electrode and extending along a periphery of the sensor electrode. The cover substrate includes one or plural conductive layers extending along the periphery of the sensor electrode and the plural signal wirings within an area not facing the sensor electrode and the plural signal wirings.
    Type: Grant
    Filed: May 10, 2023
    Date of Patent: July 30, 2024
    Assignee: Japan Display Inc.
    Inventors: Takeshi Kurashima, Shoji Hinata
  • Publication number: 20240242242
    Abstract: An incentive optimization method according to an embodiment provides an incentive optimization method for optimizing an incentive granting method for a behavior of an individual, the incentive optimization method including being executable on a computer and including: estimating a parameter of a model for each individual, the model using the incentive granting method as input and outputting a degree of achievement with respect to a target behavior, by using a sequence of the behavior and observation data of the incentive granting method with respect to the sequence; and calculating an incentive granting method that maximizes the degree of achievement using the model in which the estimated parameter is set.
    Type: Application
    Filed: May 13, 2021
    Publication date: July 18, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Hideaki KIN, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20240232646
    Abstract: A learning device for predicting an occurrence of an event includes a memory and a processor configured to divide a support set extracted from a set of previous data for learning into a plurality of sections, output a first latent vector based on each of the plurality of divided sections and output a second latent vector based on each of the output first latent vectors, and output an intensity function indicating a likelihood of the event occurring based on the second latent vector.
    Type: Application
    Filed: May 7, 2021
    Publication date: July 11, 2024
    Inventors: Yoshiaki TAKIMOTO, Takeshi KURASHIMA, Yusuke TANAKA, Tomoharu IWATA
  • Publication number: 20240221883
    Abstract: Provided is a prediction apparatus for predicting a health-oriented behavior tendency of a prediction object, the prediction apparatus including: a health-oriented behavior estimation model storage unit that stores a health-oriented behavior estimation model for estimating a health-oriented behavior based on a relationship between a health-oriented behavior and human characteristics; a human characteristic scale calculation unit that calculates a plurality of human characteristic scales based on human characteristic data indicating human characteristics of a prediction object; and a health-oriented behavior prediction unit that predicts a health-oriented behavior tendency based on the plurality of calculated human characteristic scales by using the health-oriented behavior estimation model.
    Type: Application
    Filed: June 2, 2021
    Publication date: July 4, 2024
    Inventors: Tomu TOMINAGA, Shuhei YAMAMOTO, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20240202274
    Abstract: An information processing apparatus includes an input unit configured to acquire input information including an initial first numerical index and a second numerical index that serves as a goal, and an improvement trajectory structuring unit configured to structure an improvement trajectory indicating a trajectory from the first numerical index to the second numerical index in time series, based on the input information.
    Type: Application
    Filed: May 26, 2021
    Publication date: June 20, 2024
    Inventors: Yasunori AKAGI, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20240153643
    Abstract: An information processing apparatus includes: a parameter estimation unit that estimates, as parameters indicating a temporal change in interest of a user, a first parameter, a second parameter, and a third parameter based on data including a past behavior of the user and an evaluation value of the behavior, the first parameter being a parameter indicating inherent constant interest of the user, the second parameter being a parameter indicating an effect that the user is influenced by a past behavior and is attracted to a behavior option, and the third parameter being a parameter indicating an effect that the user loses interest due to boredom by a past behavior; a social welfare calculation unit that calculates a value indicating social welfare of the user based on the estimated parameters; and an optimum behavior selection unit that selects an optimum behavior of the user based on the calculated value indicating social welfare and outputs data indicating the selected optimum behavior.
    Type: Application
    Filed: March 25, 2021
    Publication date: May 9, 2024
    Inventors: Yuka NISHIDA, Hideaki KIN, Takeshi KURASHIMA, Hiroyuki TODA
  • Patent number: 11899832
    Abstract: An observation streamlining apparatus includes one or more computers each including a memory and a processor configured to discriminate between an observation-necessary time slot and an observation-unnecessary time slot with an intervention measure including at least a time when a predetermined intervention is performed on a user as an input, the observation-necessary time slot indicating a time slot when a user's action or state needs to be observed, and the observation-unnecessary time slot indicating a time slot when the user's action or state does not need to be observed; and execute predetermined processing for observing the user's action or state when the observation-necessary time slot arrives.
    Type: Grant
    Filed: February 21, 2020
    Date of Patent: February 13, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Masami Takahashi, Masahiro Kojima, Takeshi Kurashima, Hiroyuki Toda
  • Publication number: 20240045921
    Abstract: A parameter estimation device for estimating a plurality of parameters used for calculating high-resolution data from aggregated data aggregated to coarse granularity, the parameter estimation device comprising: a parameter estimation unit configured to estimate a plurality of parameters that are unknown variables in a model so as to maximize a marginal likelihood based on the assumption that actually observed aggregated data is generated from the model based on a multivariate Gaussian process in which a plurality of latent Gaussian processes for a plurality of types of aggregated data in a plurality of domains are represented by linear mixing; and a storage unit configured to store the plurality of parameters, wherein the plurality of parameters include a hyperparameter of a prior distribution to a mixing coefficient used in the linear mixing.
    Type: Application
    Filed: December 10, 2020
    Publication date: February 8, 2024
    Inventors: Yusuke TANAKA, Tomoharu IWATA, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20230410807
    Abstract: A computer executes a first calculation procedure of calculating a first score regarding personality characteristics of a participant based on a questionnaire result for the participant in a group dialogue, a second calculation procedure of calculating a second score regarding an activity level of the participant in the group dialogue based on data in which contents of the group dialogue is recorded, and a third calculation procedure of calculating a third score indicating evaluation on the group dialogue by the participant based on the first score and the second score, thereby improving estimation accuracy of evaluation by each participant for the group dialogue.
    Type: Application
    Filed: November 10, 2020
    Publication date: December 21, 2023
    Inventors: Yoko TOKUNAGA, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20230401426
    Abstract: A prediction method executed by a computer including a memory and a processor, the method includes: optimizing a parameter of a second function that outputs parameters of a first function from covariates, and optimizing a parameter of a kernel function of a Gaussian process, by using a series of observation values observed in a past and a series of the covariates observed simultaneously with the observation values, wherein values obtained by non-linearly transforming the observation values by the first function follow the Gaussian process; and calculating a prediction distribution of observation values in a period in future to be predicted by using the second function and the kernel function having parameters optimized in the optimizing, and a series of covariates in the period.
    Type: Application
    Filed: November 5, 2020
    Publication date: December 14, 2023
    Inventors: Hideaki KIN, Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20230394363
    Abstract: A computer evaluates, from a first behavior history including, for each of a plurality of behaviors of a person, a time of the behavior and a numerical value indicating the person's state after the behavior, a first feature indicating a first amount of effort the person makes until the numerical value exceeds a threshold at a certain point in time; evaluates, from the first behavior history, a second feature indicating a degree of the person's habituation to a state indicated by the threshold by the certain point in time; and trains a prediction model, in which the first and second features are used as explanatory variables and a time interval from a behavior at the certain point in time to a next behavior in the first behavior history is used as an explained variable, based on the first and second features and the time interval.
    Type: Application
    Filed: December 3, 2020
    Publication date: December 7, 2023
    Inventors: Takeshi KURASHIMA, Hiroyuki TODA
  • Publication number: 20230395206
    Abstract: An information processing apparatus executes transmitting information related to a question for a user to a terminal of the user at a timing according to information indicating a characteristic of the user, information indicating experience of the user, and a history of responses by the user.
    Type: Application
    Filed: November 17, 2020
    Publication date: December 7, 2023
    Inventors: Tomu TOMINAGA, Takeshi KURASHIMA, Hiroyuki TODA, Shuhei YAMAMOTO
  • Publication number: 20230385638
    Abstract: According to an embodiment, a point process learning method executed by a computer includes: an input procedure of inputting a learning data set including at least first event data representing a series of occurrences of first events; a division procedure of dividing the first event data included in the learning data set by using a prediction time observation area including at least a time series when predicting future event occurrence; and a learning procedure of learning a model parameter including a parameter of an intensity function of a predetermined point process model by using a divided learning data set divided in the division procedure.
    Type: Application
    Filed: December 3, 2020
    Publication date: November 30, 2023
    Inventors: Yoshiaki TAKIMOTO, Takeshi KURASHIMA, Yusuke TANAKA