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    • 1. 发明申请
    • Anomaly detection based on directional data
    • 基于定向数据的异常检测
    • US20060053123A1
    • 2006-03-09
    • US11195456
    • 2005-08-02
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • G06F17/30
    • G06F17/30705
    • Properly detects an anomaly on the basis of directional data that are obtained in sequence from a monitored object. An anomaly detecting method includes: sequentially generating directional data indicating a feature of each piece of monitored data correspondingly to the monitored data which are input in sequence; calculating the dissimilarity of the directional data to a reference vector; updating a moment of the distribution of the dissimilarity appearing when the directional data is modeled with a multi-dimensional probability distribution, based on the moment already corresponding to the monitored data; calculating a parameter determining the variance of the multi-dimensional probability distribution, on the basis of the moment; calculating a threshold of the dissimilarity on the basis of the multi-dimensional probability distribution the variance of which is determined by the parameter; and detecting an anomaly in the monitored data that corresponds to the dissimilarity if the dissimilarity exceeds the threshold.
    • 根据从被监视对象顺序获得的方向数据,正确检测到异常。 异常检测方法包括:依次输出指示每一段被监视数据的特征的方向数据,与监控数据相对应地依次输入; 计算方向数据与参考矢量的不相似性; 基于已经对应于所监视的数据的时刻,更新当使用多维概率分布建模定向数据时出现的不相似性的分布的时刻; 根据时刻计算确定多维概率分布的方差的参数; 根据参数确定其方差的多维概率分布计算不相似性的阈值; 以及如果所述不相似度超过所述阈值,则检测所述监视数据中与所述不相似度相对应的异常。
    • 2. 发明授权
    • Anomaly detection based on directional data
    • 基于定向数据的异常检测
    • US08640015B2
    • 2014-01-28
    • US12145067
    • 2008-06-24
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • G06F11/00
    • G06F17/30705
    • Properly detects an anomaly on the basis of directional data that are obtained in sequence from a monitored object. An anomaly detecting method includes: sequentially generating directional data indicating a feature of each piece of monitored data correspondingly to the monitored data which are input in sequence; calculating the dissimilarity of the directional data to a reference vector; updating a moment of the distribution of the dissimilarity appearing when the directional data is modeled with a multi-dimensional probability distribution, based on the moment already corresponding to the monitored data; calculating a parameter determining the variance of the multi-dimensional probability distribution, on the basis of the moment; calculating a threshold of the dissimilarity on the basis of the multi-dimensional probability distribution the variance of which is determined by the parameter; and detecting an anomaly in the monitored data that corresponds to the dissimilarity if the dissimilarity exceeds the threshold.
    • 根据从被监视对象顺序获得的方向数据,正确检测到异常。 异常检测方法包括:依次输出指示每一段被监视数据的特征的方向数据,与监控数据相对应地依次输入; 计算方向数据与参考矢量的不相似性; 基于已经对应于所监视的数据的时刻,更新当使用多维概率分布建模定向数据时出现的不相似性的分布的时刻; 根据时刻计算确定多维概率分布的方差的参数; 根据参数确定其方差的多维概率分布计算不相似性的阈值; 以及如果所述不相似度超过所述阈值,则检测所述监视数据中与所述不相似度相对应的异常。
    • 3. 发明申请
    • ANOMALY DETECTION BASED ON DIRECTIONAL DATA
    • 基于方向数据的异常检测
    • US20080263663A1
    • 2008-10-23
    • US12145067
    • 2008-06-24
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • G06F21/00
    • G06F17/30705
    • Properly detects an anomaly on the basis of directional data that are obtained in sequence from a monitored object. An anomaly detecting method includes: sequentially generating directional data indicating a feature of each piece of monitored data correspondingly to the monitored data which are input in sequence; calculating the dissimilarity of the directional data to a reference vector; updating a moment of the distribution of the dissimilarity appearing when the directional data is modeled with a multi-dimensional probability distribution, based on the moment already corresponding to the monitored data; calculating a parameter determining the variance of the multi-dimensional probability distribution, on the basis of the moment; calculating a threshold of the dissimilarity on the basis of the multi-dimensional probability distribution the variance of which is determined by the parameter; and detecting an anomaly in the monitored data that corresponds to the dissimilarity if the dissimilarity exceeds the threshold.
    • 根据从被监视对象顺序获得的方向数据,正确检测到异常。 异常检测方法包括:依次输出指示每一段被监视数据的特征的方向数据,与监控数据相对应地依次输入; 计算方向数据与参考矢量的不相似性; 基于已经对应于所监视的数据的时刻,更新当使用多维概率分布建模定向数据时出现的不相似性的分布的时刻; 根据时刻计算确定多维概率分布的方差的参数; 根据参数确定其方差的多维概率分布计算不相似性的阈值; 以及如果所述不相似度超过所述阈值,则检测所述监视数据中与所述不相似度相对应的异常。
    • 4. 发明授权
    • Anomaly detection based on directional data
    • 基于定向数据的异常检测
    • US07406653B2
    • 2008-07-29
    • US11195456
    • 2005-08-02
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • Tsuyoshi IdeKeisuke InoueToshiyuki YamaneHironori Takeuchi
    • H03M13/00H04L1/00
    • G06F17/30705
    • Properly detects an anomaly on the basis of directional data that are obtained in sequence from a monitored object. An anomaly detecting method includes: sequentially generating directional data indicating a feature of each piece of monitored data correspondingly to the monitored data which are input in sequence; calculating the dissimilarity of the directional data to a reference vector; updating a moment of the distribution of the dissimilarity appearing when the directional data is modeled with a multi-dimensional probability distribution, based on the moment already corresponding to the monitored data; calculating a parameter determining the variance of the multi-dimensional probability distribution, on the basis of the moment; calculating a threshold of the dissimilarity on the basis of the multi-dimensional probability distribution the variance of which is determined by the parameter; and detecting an anomaly in the monitored data that corresponds to the dissimilarity if the dissimilarity exceeds the threshold.
    • 根据从被监视对象顺序获得的方向数据,正确检测到异常。 异常检测方法包括:依次输出指示每一段被监视数据的特征的方向数据,与监控数据相对应地依次输入; 计算方向数据与参考矢量的不相似性; 基于已经对应于所监视的数据的时刻,更新当使用多维概率分布建模方向数据时出现的不相似性的分布的时刻; 根据时刻计算确定多维概率分布的方差的参数; 根据参数确定其方差的多维概率分布计算不相似性的阈值; 以及如果所述不相似度超过所述阈值,则检测所述监视数据中与所述不相似度相对应的异常。
    • 5. 发明授权
    • Diagnostic data detection and control
    • 诊断数据检测和控制
    • US07720640B2
    • 2010-05-18
    • US11674145
    • 2007-02-13
    • Keisuke InoueTsuyoshi Ide
    • Keisuke InoueTsuyoshi Ide
    • G06F11/30
    • G05B23/0232G05B2219/32187Y02P90/22
    • Provides a diagnostic apparatus for diagnosing a measured object based on time-series data of a plurality of parameters measured from the measured object. An example of an apparatus includes a change-point score calculating portion for calculating a time-series change-point score with which each of the plurality of parameters changes according to passage of time based on the time-series data on the parameter, a change-point correlation calculating portion for calculating a change-point correlation indicating strength by which each of the plurality of parameters is associated with each of other parameters based on the change-point scores of the parameter and the other parameter, and a parameter outputting portion for outputting a set of parameters of which calculated degrees of associations are higher than a predetermined reference change-point correlation as a set of mutually strongly associated parameters.
    • 提供一种诊断装置,用于根据从测量对象测量的多个参数的时间序列数据来诊断测量对象。 一种装置的例子包括:变化点分数计算部分,用于根据参数的时间序列数据,计算多个参数中的每个参数根据时间的变化而变化的时间序列变化点得分,变化点分数计算部分, 点相关计算部分,用于基于参数和另一参数的变化点得分,计算指示多个参数中的每一个与其他参数中的每一个相关联的强度的变化点相关性;以及参数输出部分, 将相关联的计算度的一组参数作为相互强烈相关的参数的集合输出,所述一组参数高于预定的参考变化点相关性。
    • 6. 发明授权
    • Diagnostic data detection and control
    • 诊断数据检测和控制
    • US07181365B2
    • 2007-02-20
    • US11077285
    • 2005-03-10
    • Keisuke InoueTsuyoshi Ide
    • Keisuke InoueTsuyoshi Ide
    • G06F11/30
    • G05B23/0232G05B2219/32187Y02P90/22
    • Provides a diagnostic apparatus for diagnosing a measured object based on time-series data of a plurality of parameters measured from the measured object. An example of an apparatus includes a change-point score calculating portion for calculating a time-series change-point score with which each of the plurality of parameters changes according to passage of time based on the time-series data on the parameter, a change-point correlation calculating portion for calculating a change-point correlation indicating strength by which each of the plurality of parameters is associated with each of other parameters based on the change-point scores of the parameter and the other parameter, and a parameter outputting portion for outputting a set of parameters of which calculated degrees of associations are higher than a predetermined reference change-point correlation as a set of mutually strongly associated parameters.
    • 提供一种诊断装置,用于根据从测量对象测量的多个参数的时间序列数据来诊断测量对象。 一种装置的例子包括:变化点分数计算部分,用于根据参数的时间序列数据,计算多个参数中的每个参数根据时间的变化而变化的时间序列变化点得分,变化点分数计算部分, 点相关计算部分,用于基于参数和另一参数的变化点得分,计算指示多个参数中的每一个与其他参数中的每一个相关联的强度的变化点相关性;以及参数输出部分, 将相关联的计算度的一组参数作为相互强烈相关的参数的集合输出,所述一组参数高于预定的参考变化点相关性。
    • 7. 发明申请
    • Diagnostic Data Detection and Control
    • 诊断数据检测和控制
    • US20070129912A1
    • 2007-06-07
    • US11674145
    • 2007-02-13
    • Keisuke InoueTsuyoshi Ide
    • Keisuke InoueTsuyoshi Ide
    • G21C17/00
    • G05B23/0232G05B2219/32187Y02P90/22
    • Provides a diagnostic apparatus for diagnosing a measured object based on time-series data of a plurality of parameters measured from the measured object. An example of an apparatus includes a change-point score calculating portion for calculating a time-series change-point score with which each of the plurality of parameters changes according to passage of time based on the time-series data on the parameter, a change-point correlation calculating portion for calculating a change-point correlation indicating strength by which each of the plurality of parameters is associated with each of other parameters based on the change-point scores of the parameter and the other parameter, and a parameter outputting portion for outputting a set of parameters of which calculated degrees of associations are higher than a predetermined reference change-point correlation as a set of mutually strongly associated parameters.
    • 提供一种诊断装置,用于根据从测量对象测量的多个参数的时间序列数据来诊断测量对象。 一种装置的例子包括:变化点分数计算部分,用于根据参数的时间序列数据,计算多个参数中的每个参数根据时间的变化而变化的时间序列变化点得分,变化点分数计算部分, 点相关计算部分,用于基于参数和另一参数的变化点得分,计算指示多个参数中的每一个与其他参数中的每一个相关联的强度的变化点相关性;以及参数输出部分, 将相关联的计算度的一组参数作为相互强烈相关的参数的集合输出,所述一组参数高于预定的参考变化点相关性。
    • 8. 发明申请
    • Diagnostic data detection and control
    • 诊断数据检测和控制
    • US20050209820A1
    • 2005-09-22
    • US11077285
    • 2005-03-10
    • Keisuke InoueTsuyoshi Ide
    • Keisuke InoueTsuyoshi Ide
    • G01M17/007G01M99/00G06F11/30
    • G05B23/0232G05B2219/32187Y02P90/22
    • Provides a diagnostic apparatus for diagnosing a measured object based on time-series data of a plurality of parameters measured from the measured object. An example of an apparatus includes a change-point score calculating portion for calculating a time-series change-point score with which each of the plurality of parameters changes according to passage of time based on the time-series data on the parameter, a change-point correlation calculating portion for calculating a change-point correlation indicating strength by which each of the plurality of parameters is associated with each of other parameters based on the change-point scores of the parameter and the other parameter, and a parameter outputting portion for outputting a set of parameters of which calculated degrees of associations are higher than a predetermined reference change-point correlation as a set of mutually strongly associated parameters.
    • 提供一种诊断装置,用于根据从测量对象测量的多个参数的时间序列数据来诊断测量对象。 一种装置的例子包括:变化点分数计算部分,用于根据参数的时间序列数据,计算多个参数中的每个参数根据时间的变化而变化的时间序列变化点得分,变化点分数计算部分, 点相关计算部分,用于基于参数和另一参数的变化点得分,计算指示多个参数中的每一个与其他参数中的每一个相关联的强度的变化点相关性;以及参数输出部分, 将相关联的计算度的一组参数作为相互强烈相关的参数的集合输出,所述一组参数高于预定的参考变化点相关性。
    • 9. 发明授权
    • Scheduling method and scheduling apparatus
    • 调度方法和调度设备
    • US08375390B2
    • 2013-02-12
    • US11996361
    • 2006-05-31
    • Keisuke InoueSeiji Murata
    • Keisuke InoueSeiji Murata
    • G06F9/46
    • G06F9/526G06F9/461G06F9/4843G06F9/4881
    • Thread information is retained in a main memory. The thread information includes a bit string and last executed information. Each bit of the bit string is allocated to a thread, and the number and the value of the bit indicate the number of the thread and whether or not the thread is in an executable state, respectively. The last executed information is the number of a last executed thread. A processor rotates the bit string so that a bit indicating the last executed thread comes to the end of the bit string. It searches the rotated bit string for a bit corresponding to a thread in the executable state in succession from the top, and selects the number of the first obtained bit as the number of the next thread to be executed. Then, the thread information is updated by changing the value of the bit of this number to indicate not being executable, and setting the last executed information to the number of this bit. This operation is performed by using an atomic command.
    • 线程信息保留在主存储器中。 线程信息包括位串和最后执行的信息。 位串的每一位分配给一个线程,该位的数字和值分别表示线程的数量以及线程是否处于可执行状态。 最后执行的信息是最后执行的线程的编号。 处理器旋转位串,使得指示最后执行的线程的位到达位串的末尾。 从顶部连续地搜索与可执行状态的线程相对应的位的旋转位串,并选择第一获得位数作为要执行的下一个线程的号码。 然后,通过改变该数字的位的值来更新线程信息,以指示不可执行,并且将最后执行的信息设置为该位的编号。 该操作通过使用原子命令来执行。