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1. 发明授权

US09063987B2 Managing uncertain data using Monte Carlo techniques 有权
标题翻译：使用蒙特卡罗技术管理不确定的数据
公开(公告)号：US09063987B2
公开(公告)日：2015-06-23
申请号：US13495610
申请日：2012-06-13
申请人： Peter J Haas , Ravindranath Jampani , Christopher M Jermaine , Luis L Perez , Mingxi Wu , Fei Xu
发明人： Peter J Haas , Ravindranath Jampani , Christopher M Jermaine , Luis L Perez , Mingxi Wu , Fei Xu
IPC分类号： G06F17/30
CPC分类号： G06F17/30536
摘要： According to one embodiment of the present invention, a method for managing uncertain data is provided. The method includes specifying data uncertainty using at least one variable generation (VG) function. The VG function generates pseudorandom samples of uncertain data values. A random database based on the VG function is specified and multiple Monte Carlo instantiations of the random database are generated. Using a Monte Carlo method, a query is repeatedly executed over the multiple Monte Carlo instantiations to output a Monte Carlo method result and associated query-results. The Monte Carlo method result may then be used to estimate statistical properties of a probability distribution of the query-result.
摘要翻译：根据本发明的一个实施例，提供了一种用于管理不确定数据的方法。该方法包括使用至少一个变量生成（VG）函数来指定数据不确定性。 VG函数生成不确定数据值的伪随机样本。指定基于VG功能的随机数据库，并生成随机数据库的多个蒙特卡罗实例。使用蒙特卡罗方法，通过多个蒙特卡洛实例重复执行查询，以输出蒙特卡罗方法结果和关联的查询结果。然后可以使用蒙特卡罗方法结果来估计查询结果的概率分布的统计特性。

2. 发明申请

US20130300079A1 Reclining loop frame stacking / swivel chair 审中-公开
公开(公告)号：US20130300079A1
公开(公告)日：2013-11-14
申请号：US13894030
申请日：2013-05-14
申请人： Peter J. Haas
发明人： Peter J. Haas
IPC分类号： A47C1/023 , B62B3/00 , A47C3/04
CPC分类号： A47C1/023 , A47C3/021 , A47C3/04 , A47C7/44 , B62B3/00
摘要： A chair with a seating surface and a link with two ends connected to the seating surface. A frame with two supporting portions connected to the link and the frame can displace against a bias to allow one of the two supporting portions to move, allowing the seating surface to tilt. A flexible front is attached to a front member on the frame, the flexible front bends when the seating surface tilts. The link rotates when the supporting portions displace. The supporting portions are round and pass through round holes in the link, allowing the supporting portions to rotate within the link when the seating surface tilts. A stop connected to the seating surface and a stop connected to the frame limits the maximum tilt angle of the seating surface.

3. 发明申请

US20110040744A1 SYSTEM, METHOD, AND APPARATUS FOR SCAN-SHARING FOR BUSINESS INTELLIGENCE QUERIES IN AN IN-MEMORY DATABASE 失效
标题翻译：用于在内存数据库中进行业务智能扫描的扫描共享的系统，方法和装置
公开(公告)号：US20110040744A1
公开(公告)日：2011-02-17
申请号：US12539471
申请日：2009-08-11
申请人： Peter J. Haas , Lin Qiao , Vijayshankar Raman , Frederick R. Reiss
发明人： Peter J. Haas , Lin Qiao , Vijayshankar Raman , Frederick R. Reiss
IPC分类号： G06F17/30
CPC分类号： G06F17/30445
摘要： A computer-implemented method for scan sharing across multiple cores in a business intelligence (BI) query. The method includes receiving a plurality of BI queries, storing a block of data in a first cache, scanning the block of data in the first cache against a first batch of queries on a first processor core, and scanning the block of data against a second batch of queries on a second processor core. The first cache is associated with a first processor core. The block of data includes a subset of data stored in an in-memory database (IMDB). The first batch of queries includes two or more of the BI queries. The second batch of queries includes one or more of the BI queries that are not included in the first batch of queries.
摘要翻译：一种用于在商业智能（BI）查询中跨多个核心进行扫描共享的计算机实现的方法。该方法包括接收多个BI查询，将数据块存储在第一高速缓存中，针对第一处理器核心上的第一批查询扫描第一高速缓存中的数据块，并且针对第二缓冲区扫描数据块批次在第二个处理器核心上的查询。第一缓存与第一处理器核心相关联。数据块包括存储在内存数据库（IMDB）中的数据子集。第一批查询包括两个或多个BI查询。第二批查询包括未包含在第一批查询中的一个或多个BI查询。

4. 发明授权

US07836356B2 Method for monitoring dependent metric streams for anomalies 有权
标题翻译：用于监视异常的相关度量流的方法
公开(公告)号：US07836356B2
公开(公告)日：2010-11-16
申请号：US12110851
申请日：2008-04-28
申请人： Peter J. Haas , John M. Lake , Guy M. Lohman , Ashutosh Singh , Tanveer F. Syeda-Mahmood
发明人： Peter J. Haas , John M. Lake , Guy M. Lohman , Ashutosh Singh , Tanveer F. Syeda-Mahmood
IPC分类号： G06F11/00
CPC分类号： G06F11/008
摘要： A method for monitoring dependent metric streams for anomalies including identifying a plurality of sets of dependent metric streams from a plurality of metric streams of a computer system by measuring an association of the plurality of metric streams using a statistical dependency measure analysis, wherein each set includes a plurality of the dependent metric streams and each metric stream includes a plurality of data, determining a subset of the plurality of sets of dependent metric streams to monitor by selecting a quantity of the sets of dependent metric streams that have a highest statistical dependency, cleaning the data of each set of dependent metric streams of the subset by identifying and removing outlier data, fitting a probability density function to the cleaned data of each set of dependent metric streams of the subset, wherein the probability density function is a likelihood function that provides a likelihood of an occurrence of the cleaned data, determining a detection threshold that is a lower threshold on the likelihood of the occurrence of the cleaned data of each set of dependent metric streams of the subset based on the likelihood function, detecting an anomaly if a likelihood of an occurrence of a new data of one of the sets of dependent metric streams of the subset is less than the detection threshold, and transmitting an alert signal in response to detecting the anomaly.
摘要翻译：一种用于监视异常的相关度量流的方法，包括通过使用统计依赖度量度分析来测量多个度量流的关联来从计算机系统的多个度量流中识别多个独立度量流集合，其中每个集合包括多个依赖度量流和每个度量流包括多个数据，通过选择具有最高统计依赖性的依赖度量流集合的数量来确定多个依赖度量流集合的子集以进行监视通过识别和去除异常值数据，将概率密度函数拟合到子集的每组非依赖度量流的清除数据，其中概率密度函数是提供清除数据的发生的可能性，确定检测阈值，其是基于似然函数发生子集的每组非依赖度量流的清除数据的可能性的较低阈值，如果发生了一组中的一个的新数据的可能性，则检测异常所述子集的依赖度量流小于所述检测阈值，并且响应于检测到所述异常而发送警报信号。

5. 发明申请

US20090175544A1 FINDING STRUCTURES IN MULTI-DIMENSIONAL SPACES USING IMAGE-GUIDED CLUSTERING 失效
标题翻译：使用图像聚类在多维空间中寻找结构
公开(公告)号：US20090175544A1
公开(公告)日：2009-07-09
申请号：US12143131
申请日：2008-06-20
申请人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy Lohman
发明人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy Lohman
IPC分类号： G06K9/62
CPC分类号： G06K9/6219 , Y10S707/99933 , Y10S707/99945
摘要： A data processing system is provided that comprises a processor, a random access memory for storing data and programs for execution by the processor, and computer readable instructions stored in the random access memory for execution by the processor to perform a method for clustering data points in a multidimensional dataset in a multidimensional image space. The method comprises generating a multidimensional image from the multidimensional dataset; generating a pyramid of multidimensional images having varying resolution levels by successively performing a pyramidal sub-sampling of the multidimensional image; identifying data clusters at each resolution level of the pyramid by applying a set of perceptual grouping constraints; and determining levels of a clustering hierarchy by identifying each salient bend in a variation curve of a magnitude of identified data clusters as a function of pyramid resolution level.
摘要翻译：提供了一种数据处理系统，其包括处理器，用于存储用于由处理器执行的数据和程序的随机存取存储器，以及存储在随机存取存储器中的计算机可读指令，用于由处理器执行以执行将数据点聚类的方法多维图像空间中的多维数据集。该方法包括从多维数据集生成多维图像; 通过连续执行所述多维图像的锥体子采样来生成具有不同分辨率水平的多维图像的金字塔; 通过应用一组感知分组约束来识别金字塔的每个分辨率级别的数据集群; 以及通过将所识别的数据簇的幅度的变化曲线中的每个显着弯曲值确定为金字塔分辨率级别的函数来确定聚类层级的水平。

6. 发明授权

US07542954B1 Data classification by kernel density shape interpolation of clusters 有权
标题翻译：通过核心密度形状插值进行数据分类
公开(公告)号：US07542954B1
公开(公告)日：2009-06-02
申请号：US12164532
申请日：2008-06-30
申请人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
发明人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
IPC分类号： G06F17/00 , G06F15/00 , G06F15/18 , G06N5/00
CPC分类号： G06K9/6273 , G06K9/6226 , G06N99/005
摘要： A method for representing a dataset comprises clustering the dataset using an unsupervised, non-parametric clustering method to generate a set of clusters each comprising a set of data points in an image; clustering the data points of each cluster using a supervised, partitional clustering method to partition each cluster into a specified number of sub-clusters; generating a density estimate value of each grid point of a set of grid points sampled from the image at a specified resolution for each sub-cluster using a kernel density function; identifying a maximum density estimate value and a sub-cluster associated with the maximum density estimate value for the grid point; adding each grid point for which the maximum density estimate value exceeds a specified threshold to the sub-cluster associated with the maximum density estimate value; and, for each cluster, merging the sub-clusters of the cluster into a corresponding cluster region in the image.
摘要翻译：一种用于表示数据集的方法包括使用无监督的非参数聚类方法对所述数据集进行聚类，以生成每组包括图像中的一组数据点的一组聚类; 使用受监督的分段聚类方法对每个集群的数据点进行聚类，以将每个集群分成指定数量的子集群; 使用核密度函数生成以每个子群体以指定分辨率从图像采样的一组网格点的每个网格点的密度估计值; 识别最大密度估计值和与所述网格点的最大密度估计值相关联的子簇; 将最大密度估计值超过特定阈值的每个网格点添加到与最大密度估计值相关联的子簇; 并且对于每个集群，将集群的子集合合并到图像中的相应集群区域中。

7. 发明授权

US07406200B1 Method and system for finding structures in multi-dimensional spaces using image-guided clustering 失效
标题翻译：使用图像引导聚类在多维空间中寻找结构的方法和系统
公开(公告)号：US07406200B1
公开(公告)日：2008-07-29
申请号：US11970946
申请日：2008-01-08
申请人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
发明人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
IPC分类号： G06K9/62 , G06F7/00 , G06F17/30 , G06F17/00
CPC分类号： G06K9/6219 , Y10S707/99933 , Y10S707/99945
摘要： A method is provided clustering data points in a multidimensional dataset in a multidimensional image space that comprises generating a multidimensional image from the multidimensional dataset; generating a pyramid of multidimensional images having varying resolution levels by successively performing a pyramidal sub-sampling of the multidimensional image; identifying data clusters at each resolution level of the pyramid by applying a set of perceptual grouping constraints; and determining levels of a clustering hierarchy by identifying each salient bend in a variation curve of a magnitude of identified data clusters as a function of pyramid resolution level.
摘要翻译：提供了一种在多维图像空间中的多维数据集中聚类数据点的方法，其包括从多维数据集生成多维图像; 通过连续执行所述多维图像的锥体子采样来生成具有不同分辨率水平的多维图像的金字塔; 通过应用一组感知分组约束来识别金字塔的每个分辨率级别的数据集群; 以及通过将所识别的数据簇的幅度的变化曲线中的每个显着弯曲值确定为金字塔分辨率级别的函数来确定聚类层级的水平。

8. 发明授权

US6003942A Mechanism for reclining chairs 失效
标题翻译：斜倚椅子的机制
公开(公告)号：US6003942A
公开(公告)日：1999-12-21
申请号：US173526
申请日：1998-10-15
申请人： Peter J. Haas
发明人： Peter J. Haas
IPC分类号： A47C1/032
CPC分类号： A47C3/04 , A47C1/03255 , A47C1/03277 , A47C1/121 , A47C11/005 , A47C4/44
摘要： A reclining chair has a seat and a chair back both tiltably carried on a base. The chair back is provided with lever means for tilting the seat as the chair back is tilted. The lever means contacts the seat at a point which moves in response to the tilting of the chair back. Advantageously, the seat includes a contact portion, adapted for engagement with the lever means, which is configured to provide a predetermined displacement of the seat in response to displacement of the chair back.
摘要翻译：一个躺椅有一个座椅和一个椅子，两个可倾斜地承载在基座上。椅背设置有杠杆装置，用于在座椅靠背倾斜时倾斜座椅。杠杆装置在响应于椅背的倾斜而移动的点处接触座椅。有利地，座椅包括适于与杠杆装置接合的接触部分，其被构造成响应于座椅背部的位移而提供座椅的预定位移。

9. 发明授权

US07558425B1 Finding structures in multi-dimensional spaces using image-guided clustering 失效
标题翻译：使用图像引导聚类在多维空间中寻找结构
公开(公告)号：US07558425B1
公开(公告)日：2009-07-07
申请号：US12143131
申请日：2008-06-20
申请人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
发明人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
IPC分类号： G06K9/62 , G06F7/00 , G06F17/00 , G06F17/30
CPC分类号： G06K9/6219 , Y10S707/99933 , Y10S707/99945
摘要： A data processing system is provided that comprises a processor, a random access memory for storing data and programs for execution by the processor, and computer readable instructions stored in the random access memory for execution by the processor to perform a method for clustering data points in a multidimensional dataset in a multidimensional image space. The method comprises generating a multidimensional image from the multidimensional dataset; generating a pyramid of multidimensional images having varying resolution levels by successively performing a pyramidal sub-sampling of the multidimensional image; identifying data clusters at each resolution level of the pyramid by applying a set of perceptual grouping constraints; and determining levels of a clustering hierarchy by identifying each salient bend in a variation curve of a magnitude of identified data clusters as a function of pyramid resolution level.
摘要翻译：提供了一种数据处理系统，其包括处理器，用于存储用于由处理器执行的数据和程序的随机存取存储器，以及存储在随机存取存储器中的计算机可读指令，用于由处理器执行以执行将数据点聚类的方法多维图像空间中的多维数据集。该方法包括从多维数据集生成多维图像; 通过连续执行所述多维图像的锥体子采样来生成具有不同分辨率水平的多维图像的金字塔; 通过应用一组感知分组约束来识别金字塔的每个分辨率级别的数据集群; 以及通过将所识别的数据簇的幅度的变化曲线中的每个显着弯曲值确定为金字塔分辨率级别的函数来确定聚类层级的水平。

10. 发明授权

US07542953B1 Data classification by kernel density shape interpolation of clusters 有权
标题翻译：通过核心密度形状插值进行数据分类
公开(公告)号：US07542953B1
公开(公告)日：2009-06-02
申请号：US12142949
申请日：2008-06-20
申请人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
发明人： Tanveer Syeda-Mahmood , Peter J. Haas , John M. Lake , Guy M. Lohman
IPC分类号： G06F17/00 , G06F15/00 , G06F15/18 , G06N5/00
CPC分类号： G06K9/6273 , G06K9/6226 , G06N99/005
摘要： A data processing system is provided that comprises a processor, a random access memory for storing data and programs for execution by the processor, and computer readable instructions stored in the random access memory for execution by the processor to perform a method for obtaining a shape interpolated representation of shapes of clusters in an image of a clustered dataset. The method comprises generating a density estimate value of each grid point of a set of grid points sampled from the image at a specified resolution for each cluster using a kernel density function; evaluating the density estimate value of each grid point for each cluster to identify a maximum density estimate value of each grid point and a cluster associated with the maximum density estimate value; and adding each grid point for which the maximum density estimate value exceeds a specified threshold to the associated cluster to form a shape interpolated representation.
摘要翻译：提供了一种数据处理系统，其包括处理器，用于存储用于由处理器执行的数据和程序的随机存取存储器以及存储在随机存取存储器中的计算机可读指令，以供处理器执行以执行用于获得内插形状的方法聚类数据集的图像中的聚类形状的表示。该方法包括使用核密度函数，以每个簇的特定分辨率从图像采样的一组网格点的每个网格点的密度估计值; 评估每个簇的每个网格点的密度估计值，以识别每个网格点的最大密度估计值和与最大密度估计值相关联的簇; 并将最大密度估计值超过规定阈值的每个网格点添加到相关联的簇以形成形状插值表示。

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