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    • 1. 发明申请
    • METHOD AND APPARATUS FOR PREDICTING OBJECT PROPERTIES AND EVENTS USING SIMILARITY-BASED INFORMATION RETRIEVAL AND MODELING
    • 使用基于相似性的信息检索和建模来预测对象属性和事件的方法和装置
    • US20100332210A1
    • 2010-12-30
    • US12823320
    • 2010-06-25
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. HornMark Rader
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. HornMark Rader
    • G06F9/45G06F17/30
    • G06Q30/0185G06F17/30321G06F17/30424G06F17/30442G06F17/30598G06F17/30657G06F17/3071G06K9/6224G06K9/6253G06Q50/265
    • Method and apparatus for predicting properties of a target object, in particular, one of an origin and a source, comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, a fire event and residual objects may be located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.
    • 用于预测目标对象,特别是源和源之一的属性的方法和装置包括:用于分析多个对象的多个数据库的参数的搜索管理器的应用,所述数据库包括电,电磁, 声谱数据库(ESD),微体组合数据库(MAD)和图像数据数据库,由此数据库存储包含识别特征的数据对象,源信息和关于站点属性和包括时间和频率变化数据的上下文的信息。 该方法包括应用多变量统计分析和主成分分析与基于内容的图像检索相结合,以提供三维对象的二维属性,例如,通过使用形状树的优先图像分割并预测对象的进一步属性 通过k-means聚类和相关方法。 作为示例,火灾事件和残余物体可以被定位和限定,使得例如残留物体的性质可以是合格的,例如通过黑体辐射和包括木炭组合的微体数据库。
    • 2. 发明授权
    • Method and apparatus for predicting object properties and events using similarity-based information retrieval and modeling
    • 使用基于相似性的信息检索和建模来预测对象属性和事件的方法和装置
    • US08375032B2
    • 2013-02-12
    • US12823320
    • 2010-06-25
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. HornMark S. Rader
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. HornMark S. Rader
    • G06F7/00G06F17/30
    • G06Q30/0185G06F17/30321G06F17/30424G06F17/30442G06F17/30598G06F17/30657G06F17/3071G06K9/6224G06K9/6253G06Q50/265
    • Method and apparatus for predicting properties of a target object, in particular, one of an origin and a source, comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, a fire event and residual objects may be located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.
    • 用于预测目标对象,特别是源和源之一的属性的方法和装置包括:用于分析多个对象的多个数据库的参数的搜索管理器的应用,所述数据库包括电,电磁, 声谱数据库(ESD),微体组合数据库(MAD)和图像数据数据库,由此数据库存储包含识别特征的数据对象,源信息和关于站点属性和包括时间和频率变化数据的上下文的信息。 该方法包括应用多变量统计分析和主成分分析与基于内容的图像检索相结合,以提供三维对象的二维属性,例如,通过使用形状树的优先图像分割并预测对象的进一步属性 通过k-means聚类和相关方法。 作为示例,火灾事件和残余物体可以被定位和限定,使得例如残留物体的性质可以是合格的,例如通过黑体辐射和包括木炭组合的微体数据库。
    • 3. 发明授权
    • Method and apparatus for predicting object properties and events using similarity-based information retrieval and model
    • 使用基于相似性的信息检索和模型预测对象属性和事件的方法和装置
    • US08392418B2
    • 2013-03-05
    • US12823284
    • 2010-06-25
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. Horn
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. Horn
    • G06F7/00G06F17/30
    • G06Q30/0185G06F17/30321G06F17/30424G06F17/30442G06F17/30598G06F17/30657G06F17/3071G06K9/6224G06K9/6253G06Q50/265
    • Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a process failure event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.
    • 用于预测目标对象的属性的方法和装置包括应用用于分析多个对象的多个数据库的参数的搜索管理器,所述数据库包括电,电磁,声谱数据库(ESD),微体组合 数据库(MAD)和图像数据的数据库,由此数据库存储包含识别特征的数据对象,源信息和关于站点属性和包括时间和频率变化数据的上下文的信息。 该方法包括应用多变量统计分析和主成分分析与基于内容的图像检索相结合,以提供三维对象的二维属性,例如,通过使用形状树的优先图像分割并预测对象的进一步属性 通过k-means聚类和相关方法。 作为示例,可以预测和定位过程失败事件,入侵事件和火灾事件以及残余对象中的一个,使得例如残留对象的属性可以被限定,例如通过黑体 辐射和微体数据库,包括木炭组合。
    • 4. 发明申请
    • METHOD AND APPARATUS FOR PREDICTING OBJECT PROPERTIES AND EVENTS USING SIMILARITY-BASED INFORMATION RETRIEVAL AND MODEL
    • 使用基于相似性的信息检索和模型预测对象属性和事件的方法和装置
    • US20100332474A1
    • 2010-12-30
    • US12823284
    • 2010-06-25
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. Horn
    • J. Douglas BirdwellTse-Wei WangDavid J. IcoveSally P. Horn
    • G06F17/30
    • G06Q30/0185G06F17/30321G06F17/30424G06F17/30442G06F17/30598G06F17/30657G06F17/3071G06K9/6224G06K9/6253G06Q50/265
    • Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a process failure event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.
    • 用于预测目标对象的属性的方法和装置包括应用用于分析多个对象的多个数据库的参数的搜索管理器,所述数据库包括电,电磁,声谱数据库(ESD),微体组合 数据库(MAD)和图像数据的数据库,由此数据库存储包含识别特征的数据对象,源信息和关于站点属性和包括时间和频率变化数据的上下文的信息。 该方法包括应用多变量统计分析和主成分分析与基于内容的图像检索相结合,以提供三维对象的二维属性,例如,通过使用形状树的优先图像分割并预测对象的进一步属性 通过k-means聚类和相关方法。 作为示例,可以预测和定位过程失败事件,入侵事件和火灾事件以及残余对象中的一个,使得例如残留对象的属性可以被限定,例如通过黑体 辐射和微体数据库,包括木炭组合。
    • 9. 发明授权
    • Parallel data processing architecture
    • 并行数据处理架构
    • US07454411B2
    • 2008-11-18
    • US10767776
    • 2004-01-30
    • John D. BirdwellTse-Wei WangRoger D. HornPuneet YadavDavid J. Icove
    • John D. BirdwellTse-Wei WangRoger D. HornPuneet YadavDavid J. Icove
    • G06F17/30G06F7/00G06F17/00
    • G06F17/30327G06F17/30333G06F17/30598G06F19/24G06F19/28Y10S707/99932Y10S707/99933Y10S707/99935Y10S707/99942Y10S707/99945
    • A tree-structured index to multidimensional data is created using naturally occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of naturally occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps naturally to parallel computer architectures, allowing scale up to very large databases.
    • 使用数据中的自然发生的模式和集群创建树形结构的多维数据索引,这些数据允许DNA简档数据库中的高效搜索和检索策略。 搜索引擎利用数据库的分层分解,通过识别类似DNA分布的集群并将其映射到并行计算机体系结构,从而超越以前可行的限制。 新方法的主要优点是对数放大和并行化。 这些优点通过识别和利用存储数据中的自然发生的模式和集群来实现。 模式和集群使存储的数据能够被分割成大致相等大小的子集。 该方法可以递归地应用,导致数据库树是平衡的,意味着通过树的所有路径或分支具有大致相同的长度。 该方法通过以保持平衡树的方式利用数据的自然结构来实现高性能。 该方法的实现自然映射到并行计算机体系结构,允许扩展到非常大的数据库。
    • 10. 发明申请
    • Parallel Data Processing System
    • 并行数据处理系统
    • US20090055361A1
    • 2009-02-26
    • US12199010
    • 2008-08-27
    • John D. BirdwellTse-Wei WangRoger D. HornPuneet YadavDavid J. Icove
    • John D. BirdwellTse-Wei WangRoger D. HornPuneet YadavDavid J. Icove
    • G06F17/30
    • G06F17/30327G06F17/30333G06F17/30598G06F19/24G06F19/28Y10S707/99932Y10S707/99933Y10S707/99935Y10S707/99942Y10S707/99945
    • A tree-structured index to multidimensional data is created using naturally occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of naturally occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps naturally to parallel computer architectures, allowing scale up to very large databases.
    • 使用数据中的自然发生的模式和集群创建树形结构的多维数据索引,这些数据允许DNA简档数据库中的高效搜索和检索策略。 搜索引擎利用数据库的分层分解,通过识别类似DNA分布的集群并将其映射到并行计算机体系结构,从而超越以前可行的限制。 新方法的主要优点是对数放大和并行化。 这些优点通过识别和利用存储数据中的自然发生的模式和集群来实现。 模式和集群使存储的数据能够被划分成大致相等大小的子集。 该方法可以递归地应用,导致数据库树是平衡的,意味着通过树的所有路径或分支具有大致相同的长度。 该方法通过以保持平衡树的方式利用数据的自然结构来实现高性能。 该方法的实现自然映射到并行计算机体系结构,允许扩展到非常大的数据库。