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公开(公告)号：US20160366723A1
公开(公告)日：2016-12-15
申请号：US15145076
申请日：2016-05-03
Applicant: International Business Machines Corporation
Inventor： Hirofumi Nishikawa , Tomohiro Shioya , Kei Sugano , Shoichiro Watanabe
IPC: H04W84/18 , H04L12/733 , H04W4/00 , H04W4/02
Abstract: A method for transferring data among communication devices. The method includes a first communication device receiving, from a second communication device, data to be transferred and a condition defining a range of data transfer. The first communication device then determines whether a third communication device satisfies the condition defining the range of data transfer. On condition that the first communication device determines that the third communication device satisfies the condition, the first communication device directly transfers the data and the condition to the third communication device.
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公开(公告)号：US20160366555A1
公开(公告)日：2016-12-15
申请号：US14739075
申请日：2015-06-15
Applicant: International Business Machines Corporation
Inventor： Hirofumi Nishikawa , Tomohiro Shioya , Kei Sugano , Shoichiro Watanabe
Abstract: A method for transferring data among communication devices. The method includes a first communication device receiving, from a second communication device, data to be transferred and a condition defining a range of data transfer. The first communication device then determines whether a third communication device satisfies the condition defining the range of data transfer. On condition that the first communication device determines that the third communication device satisfies the condition, the first communication device directly transfers the data and the condition to the third communication device.
Abstract translation: 一种用于在通信设备之间传送数据的方法。 该方法包括从第二通信设备接收要传送的数据和定义数据传送范围的条件的第一通信设备。 然后，第一通信设备确定第三通信设备是否满足定义数据传送范围的条件。 在第一通信设备确定第三通信设备满足条件的条件下，第一通信设备直接将数据和条件传送到第三通信设备。
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公开(公告)号：US09467839B1
公开(公告)日：2016-10-11
申请号：US14970600
申请日：2015-12-16
Applicant: International Business Machines Corporation
Inventor： Yasutaka Nishimura , Hiroya Ogihara , Takahito Tashiro , Shoichiro Watanabe
CPC classification number: H04W4/90 , G06F17/30241 , H04L12/1845 , H04L67/12 , H04W4/02 , H04W4/021 , H04W4/04 , H04W4/046 , H04W4/30 , H04W4/40 , H04W76/50
Abstract: A system includes a plurality of subsystems respectively assigned to a plurality of regions in a geographic space, the plurality of subsystems including a first subsystem assigned to a first region of the plurality of regions. The first subsystem includes a first event server operable to generate a first dynamic event agent for handling a dynamic event occurring in the first region, the first dynamic event agent operable to issue a request to a second subsystem, of the plurality of subsystems, assigned to a second region next to the first region, the request causing a second event server of the second subsystem to generate a second dynamic event agent for handling the dynamic event in the second region. The first subsystem further includes a first mobile object server operable to transmit a signal based on information about the dynamic event to a mobile object in the first region.
Abstract translation: 系统包括分配给地理空间中的多个区域的多个子系统，所述多个子系统包括分配给多个区域中的第一区域的第一子系统。 第一子系统包括第一事件服务器，其可操作以生成用于处理在第一区域中发生的动态事件的第一动态事件代理，第一动态事件代理可操作以向多个子系统中的第二子系统发出分配给 所述第二区域的第二区域，所述请求导致所述第二子系统的第二事件服务器生成用于处理所述第二区域中的所述动态事件的第二动态事件代理。 第一子系统还包括第一移动对象服务器，其可操作以基于关于动态事件的信息将信号发送到第一区域中的移动对象。
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公开(公告)号：US20230050708A1
公开(公告)日：2023-02-16
申请号：US17402764
申请日：2021-08-16
Applicant: International Business Machines Corporation
Inventor： Shoichiro Watanabe , Kenichi Takasaki , Mari Abe Fukuda , Sanehiro Furuichi , Yasutaka Nishimura
Abstract: A computer system trains a federated learning model. A federated learning model is distributed to a plurality of computing nodes, each having a set of local training data comprising labeled data samples. Statistical data is received from each computing node that indicates the node's count of data samples for each label, and is analyzed to identify one or more computing nodes having local training data in which a label category is underrepresented beyond a threshold value with respect to data samples. Additional data samples labeled with the underrepresented labels are provided, and the computing nodes perform training. Results of training are received and are processed to generate a trained global model. Embodiments of the present invention further include a method and program product for training a federated learning model in substantially the same manner described above.
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公开(公告)号：US20220343219A1
公开(公告)日：2022-10-27
申请号：US17302187
申请日：2021-04-27
Applicant: International Business Machines Corporation
Inventor： Kenichi Takasaki , Shoichiro Watanabe , Mari Abe Fukuda , Sanehiro Furuichi , Yasutaka Nishimura
Abstract: A computer-implemented method, a computer program product, and a computer system for parallel cross validation in collaborative machine learning. A server groups local models into groups. In each group, each local device uses its local data to validate accuracies of the local models and sends a validation result to a group leader or the server. The group leader or the server selects groups whose variances of the accuracies are not below a predetermined variance threshold. In each selected group, the group leader or the server compares an accuracy of each local model with an average value of the accuracies and randomly selects one or more local models whose accuracies do not exceed a predetermined accuracy threshold. The server obtains weight parameters of selected local models and updates the global model based on the weight parameters.
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Patent Agency Ranking
公开(公告)号：US20220292955A1
公开(公告)日：2022-09-15
申请号：US17198893
申请日：2021-03-11
Applicant: International Business Machines Corporation
Inventor： Kenichi Takasaki , Shoichiro Watanabe , Sanehiro Furuichi , Yasutaka Nishimura
IPC: G08G1/01
Abstract: A method for calculating traffic flow changes includes detecting a traffic event. The method further includes determining an affected area of the traffic event and determining an investigation area based on the affected area. The method further includes selecting at least one vehicle located within the investigation area and calculating a change in traffic flow due to the traffic event based on a comparison of a predicted traffic flow with a current traffic flow, wherein the current traffic flow is based on information received from the at least one vehicle. The method further includes updating the affected area based on the change in traffic flow and calculating an updated change in traffic flow based on the updated affected area when the updated affected area is larger than a predetermined threshold area.
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公开(公告)号：US11200286B1
公开(公告)日：2021-12-14
申请号：US16878660
申请日：2020-05-20
Applicant: International Business Machines Corporation
Inventor： Sanehiro Furuichi , Shoichiro Watanabe , Kenichi Takasaki , Yasutaka Nishimura
IPC: G06F16/00 , G06F16/909 , G06F9/54 , G06F16/9035
Abstract: Described are techniques for acquiring geospatial data according to an information value. The techniques including determining a context for geospatial data to be used in an application, where the context is based on one or more external factors that influence variation of the geospatial data. The techniques further include calculating an information value of the geospatial data in the context for each of a plurality of information acquisition methods, where the plurality of information acquisition methods include respective data acquisition frequencies and respective spatial resolutions, and where the information value is based on an information loss function, an information amount, and a cost. The techniques further include selecting a first information acquisition method with a highest information value and acquiring the geospatial data using the first information acquisition method.
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公开(公告)号：US11079238B2
公开(公告)日：2021-08-03
申请号：US16202380
申请日：2018-11-28
Applicant: International Business Machines Corporation
Inventor： Yasutaka Nishimura , Shoichiro Watanabe , Sanehiro Furuichi , Kenichi Takasaki
Abstract: A method of calculating a most probable path (MPP) comprising: with a classification module, classifying each of a plurality of origin and destination (O/D) trajectories into one of a plurality of periods of time, the classification comprising: changing a data sampling time period of any of the plurality of trajectories within the determined classification periods; with the classification module, detecting any O/D data descriptive of an aperiodic O/D trajectory using context data descriptive of the aperiodic O/D trajectory; and with the classification module, calculating a route trajectory serving as a candidate of the MPP to determine a priority O/D trajectory that matches the context data.
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公开(公告)号：US10969235B2
公开(公告)日：2021-04-06
申请号：US16190286
申请日：2018-11-14
Applicant: International Business Machines Corporation
Inventor： Sanehiro Furuichi , Yasutaka Nishimura , Kenichi Takasaki , Shoichiro Watanabe
Abstract: The method, computer program product and computer system may include computing device which may determine a destination route. The computing device may receive current travel data associated with a primary user on the destination route and determine past travel data associated with a primary user on the destination route. The computing device may calculate, in response to determining that past travel data associated with a primary user on the destination route exists, a reliability degree of the current travel data associated with a primary user on the destination route based on the past travel data associated with a primary user on the destination route. The computing device may transmit a signal to a user device, the signal providing an instruction to display features according to an abstraction level of points of interest on the destination route based on the reliability degree.
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公开(公告)号：US10915665B2
公开(公告)日：2021-02-09
申请号：US16513076
申请日：2019-07-16
Applicant: International Business Machines Corporation
Inventor： Yasutaka Nishimura , Mari Abe Fukuda , Shoichiro Watanabe
Abstract: Position data may gradually pseudonymized by a method, comprising: generating a sequence of relative positions from a sequence of absolute positions of a moving object; randomizing the sequence of relative positions using at least a sequence of random numbers generated from at least one seed; in response to receiving an analytical job comprising the at least one seed, restoring the sequence of relative positions from the randomized sequence of relative positions; and in response to receiving an analytical job comprising both the at least one seed and at least one absolute position derived from the sequence of absolute positions, restoring the sequence of absolute positions from the randomized sequence of relative positions.
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