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    • 61. 发明授权
    • Dimensionally constrained synthetic context objects database
    • 尺寸约束的合成上下文对象数据库
    • US08620958B1
    • 2013-12-31
    • US13610347
    • 2012-09-11
    • Samuel S. AdamsRobert R. FriedlanderJames R. Kraemer
    • Samuel S. AdamsRobert R. FriedlanderJames R. Kraemer
    • G06F7/00G06F17/30
    • G06F17/30539G06F7/00G06F17/30G06F17/30528G06F17/30589G06F17/30607G06F2216/03
    • A processor-implemented method, system, and/or computer program product generate and utilize a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects. A non-contextual data object is associated with a context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object. A dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects is then constructed for handling requests for data stores, where a requester requests data stores that are associated with a same dimension of the dimensionally constrained hierarchical synthetic context-based object library.
    • 处理器实现的方法,系统和/或计算机程序产品针对多个合成的基于上下文的对象生成并利用尺度上限制的层级合成基于上下文的对象库。 非上下文数据对象与上下文对象相关联以定义合成的基于上下文的对象,其中非上下文数据对象含义地涉及多个主题事件,并且其中上下文对象提供识别特定主题 - 从多个主题事件,非上下文数据对象的事情。 合成的基于上下文的对象然后与至少一个特定的数据存储相关联,该存储包括与非上下文数据对象和上下文对象中包含的数据相关联的数据。 然后构建用于多个基于合成的基于上下文的对象的基于尺寸限制的基于层级的合成基于上下文的对象库,用于处理对数据存储的请求,其中请求者请求与尺寸限制的层级合成基于上下文的对象的相同维度相关联的数据存储 图书馆。
    • 62. 发明申请
    • MINIMIZATION OF SURPRISAL DATA THROUGH APPLICATION OF HIERARCHY FILTER PATTERN
    • 通过应用层次滤波器图案来最小化数据
    • US20130311435A1
    • 2013-11-21
    • US13491884
    • 2012-06-08
    • Robert R. FriedlanderJames R. Kraemer
    • Robert R. FriedlanderJames R. Kraemer
    • G06F7/00G06F17/30
    • G06F16/1744G06F16/24578G16B30/00G16B50/00
    • A method, computer product, and computer system of minimizing surprisal data comprising: at a source, reading and identifying characteristics of a genetic sequence of an organism; receiving an input of rank of at least two identified characteristics of the genetic sequence of the organism; generating a hierarchy of ranked, identified characteristics based on the rank of the at least two identified characteristics of the genetic sequence of the organism; comparing the hierarchy of ranked, identified characteristics to a repository of reference genomes; and if at least one reference genome from the repository matches the hierarchy of ranked, identified characteristics, breaking the matched reference genomes into pieces, combining pieces associated with the identified characteristics from at least one matched reference genome to form a filter pattern to be compared to the nucleotides of the genetic sequence of the organism, to obtain differences and create surprisal data.
    • 一种使意外数据最小化的方法,计算机产品和计算机系统,包括:来源,读取和识别生物体的遗传序列的特征; 接收生物体遗传序列的至少两个识别特征的等级的输入; 基于所述生物体的遗传序列的所述至少两个识别的特征的等级来生成排名,确定的特征的层次; 将排名的,识别的特征的层级与参考基因组的储存库进行比较; 并且如果来自所述储存库的至少一个参考基因组匹配排序,鉴定的特征的分级,将所述匹配的参考基因组破碎成碎片,将与所识别的特征相关联的片段与至少一个匹配的参考基因组相组合以形成要与 生物的遗传序列的核苷酸,以获得差异并产生令人惊讶的数据。
    • 63. 发明申请
    • PARALLELIZATION OF SURPRISAL DATA REDUCTION AND GENOME CONSTRUCTION FROM GENETIC DATA FOR TRANSMISSION, STORAGE, AND ANALYSIS
    • 用于传输,存储和分析的遗传数据的平均数据简化和基因组建的并行化
    • US20130254218A1
    • 2013-09-26
    • US13428339
    • 2012-03-23
    • Robert R. FriedlanderJames R. Kraemer
    • Robert R. FriedlanderJames R. Kraemer
    • G06F17/30
    • G06F19/22
    • A method, computer product, and computer system of reducing an amount of data representing a genetic sequence of an organism, comprising: a computer dividing a reference genome and a sequence of the organism into parts and assigning the parts to one of a plurality of computer processing elements. Within each computer processing element, comparing nucleotides of the genetic sequence of the organism to nucleotides from a part of the reference genome, to find differences where nucleotides of the genetic sequence of the organism which are different from the nucleotides of the reference genome; and storing the surprisal data in a repository. Combining the parts of the surprisal data from the repository to form a complete set of surprisal data representing the differences between the genetic sequence of the organism and the reference genome; and storing the complete set of surprisal data in the repository.
    • 一种减少表示生物体的遗传序列的数据量的方法,计算机产品和计算机系统,包括:将参考基因组和所述生物体的序列划分为部分并将所述部分分配给多个计算机之一的计算机 处理元件。 在每个计算机处理元件内,将生物体的遗传序列的核苷酸与来自参考基因组的一部分的核苷酸进行比较,以发现不同于参考基因组的核苷酸的生物的遗传序列的核苷酸的差异; 并将惊奇数据存储在存储库中。 将来自储存库的惊人数据的部分组合以形成一组完整的惊人数据,这些数据表示生物体的基因序列与参照基因组之间的差异; 并将完整的惊奇数据集存储在存储库中。
    • 69. 发明授权
    • Risk assessment in a pre/post security area within an airport
    • 机场前/后安全区域的风险评估
    • US07895144B2
    • 2011-02-22
    • US11971405
    • 2008-01-09
    • Robert Lee AngellRobert R. FriedlanderJames R. Kraemer
    • Robert Lee AngellRobert R. FriedlanderJames R. Kraemer
    • G06N5/00
    • G06N5/04
    • A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a pre/post security area within an airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives inference data comprising inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.
    • 风险评估方法和制度。 该方法包括由推理机接收与位于机场内的前/后安全区域内的第一队列相关联的第一传感器队列数据。 推理机接收与第一队列相关联的第一组技术推论。 推理引擎基于第一组技术推论和第一传感器队列数据生成第一风险群组推论。 推理机接收包括与第一队列相关联的推论的推理数据。 推理引擎产生包括与第一队列相关联的第二多个推断的第二推理数据。 第二推理数据是基于推理数据和第一次风险队列推论。 推理引擎为第一个队列生成第一个相关联的风险等级得分。 计算系统存储第二推理数据和第一相关风险等级得分。
    • 70. 发明授权
    • Risk assessment between airports
    • 机场之间的风险评估
    • US07885909B2
    • 2011-02-08
    • US11971281
    • 2008-01-09
    • Robert Lee AngellRobert R. FriedlanderJames R. Kraemer
    • Robert Lee AngellRobert R. FriedlanderJames R. Kraemer
    • G06N5/00
    • G06Q30/02G06N5/04
    • A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a first airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.
    • 风险评估方法和制度。 该方法包括由推理机接收与位于第一机场内的第一队列相关联的第一传感器队列数据。 推理机接收与第一队列相关联的第一组技术推论。 推理引擎基于第一组技术推论和第一传感器队列数据生成第一风险群组推论。 所述推理机接收包括与所述第一队列相关联的第一多个推断的第一推断数据。 推理引擎产生包括与第一队列相关联的第二多个推断的第二推理数据。 第二推理数据基于第一推理数据和第一风险队列推论。 推理引擎为第一个队列生成第一个相关联的风险等级得分。 计算系统存储第二推理数据和第一相关风险等级得分。