OPTIMAL TEST FLOW SCHEDULING WITHIN AUTOMATED TEST EQUIPMENT FOR MINIMIZED MEAN TIME TO DETECT FAILURE
    1.
    发明申请
    OPTIMAL TEST FLOW SCHEDULING WITHIN AUTOMATED TEST EQUIPMENT FOR MINIMIZED MEAN TIME TO DETECT FAILURE 审中-公开
    在自动测试设备中进行最佳测试流程调度,以最小化平均时间来检测故障

    公开(公告)号:US20110288808A1

    公开(公告)日:2011-11-24

    申请号:US12784142

    申请日:2010-05-20

    IPC分类号: G06F19/00 G01R31/26

    CPC分类号: G06F11/27 G01R31/2894

    摘要: The present invention describes a method and system for optimizing a test flow within each ATE (Automated Test Equipment) station. The test flow includes a plurality of test blocks. A test block includes a plurality of individual tests. A computing system schedule the test flow based one or more of: a test failure model, test block duration and a yield model. The failure model determines an order or sequence of the test blocks. There are at least two failure models: independent failure model and dependant failure model. The yield model describes whether a semiconductor chip is defective or not. Upon completing the scheduling, the ATE station conducts tests according to the scheduled test flow. The present invention can also be applied to software testing.

    摘要翻译: 本发明描述了用于优化每个ATE(自动测试设备)站内的测试流程的方法和系统。 测试流程包括多个测试块。 测试块包括多个单独测试。 计算系统基于以下一个或多个来计划测试流程:测试失败模型,测试块持续时间和产量模型。 故障模型确定测试块的顺序或顺序。 至少有两种故障模型:独立故障模型和依赖故障模型。 产量模型描述了半导体芯片是否有缺陷。 完成调度后,ATE站根据预定的测试流程进行测试。 本发明也可以应用于软件测试。

    Method and system for predicting resource usage of reusable stream processing elements
    2.
    发明授权
    Method and system for predicting resource usage of reusable stream processing elements 有权
    用于预测可重用流处理元素资源使用的方法和系统

    公开(公告)号:US07941387B2

    公开(公告)日:2011-05-10

    申请号:US11935079

    申请日:2007-11-05

    IPC分类号: G06F17/00 G06N5/02

    CPC分类号: G06N99/005

    摘要: A method is provided for generating a resource function estimate of resource usage by an instance of a processing element configured to consume zero or more input data streams in a stream processing system having a set of available resources that comprises receiving at least one specified performance metric for the zero or more input data streams and a processing power of the set of available resources, wherein one specified performance metric is stream rate; generating a multi-part signature of executable-specific information for the processing element and a multi-part signature of context-specific information for the instance; accessing a database of resource functions to identify a static resource function corresponding to the executable-specific information and a context-dependent resource function corresponding to the context-specific information; combining the static resource function and the context-dependent resource function to form a composite resource function for the instance; and applying the resource function to the at least one specified performance metric and the processing power to generate the resource function estimate of the at least one specified performance metric for processing by the instance.

    摘要翻译: 提供了一种用于通过被配置为在具有一组可用资源的流处理系统中消耗零个或多个输入数据流的处理元件的实例来生成资源使用的资源功能估计的方法,所述流处理系统包括:一组可用资源,其包括接收至少一个指定的性能度量 零个或多个输入数据流和可用资源集合的处理能力,其中一个指定的性能度量是流速率; 生成用于处理元件的可执行特定信息的多部分签名和该实例的上下文特定信息的多部分签名; 访问资源功能的数据库以识别与所述可执行特定信息相对应的静态资源功能以及与所述上下文特定信息相对应的与上下文相关的资源功能; 结合静态资源功能和上下文相关资源功能,形成实例的复合资源功能; 以及将所述资源功能应用于所述至少一个指定的性能度量和所述处理能力,以生成所述至少一个指定的性能度量的资源功能估计,以供所述实例处理。

    METHOD AND SYSTEM FOR PREDICTING RESOURCE USAGE OF REUSABLE STREAM PROCESSING ELEMENTS
    3.
    发明申请
    METHOD AND SYSTEM FOR PREDICTING RESOURCE USAGE OF REUSABLE STREAM PROCESSING ELEMENTS 有权
    用于预测资源使用可回收流程处理元素的方法和系统

    公开(公告)号:US20090119238A1

    公开(公告)日:2009-05-07

    申请号:US11935079

    申请日:2007-11-05

    IPC分类号: G06N5/04

    CPC分类号: G06N99/005

    摘要: A method is provided for generating a resource function estimate of resource usage by an instance of a processing element configured to consume zero or more input data streams in a stream processing system having a set of available resources that comprises receiving at least one specified performance metric for the zero or more input data streams and a processing power of the set of available resources, wherein one specified performance metric is stream rate; generating a multi-part signature of executable-specific information for the processing element and a multi-part signature of context-specific information for the instance; accessing a database of resource functions to identify a static resource function corresponding to the executable-specific information and a context-dependent resource function corresponding to the context-specific information; combining the static resource function and the context-dependent resource function to form a composite resource function for the instance; and applying the resource function to the at least one specified performance metric and the processing power to generate the resource function estimate of the at least one specified performance metric for processing by the instance.

    摘要翻译: 提供了一种用于通过被配置为在具有一组可用资源的流处理系统中消耗零个或多个输入数据流的处理元件的实例来生成资源使用的资源功能估计的方法,所述流处理系统包括:一组可用资源,其包括接收至少一个指定的性能度量 零个或多个输入数据流和可用资源集合的处理能力,其中一个指定的性能度量是流速率; 生成用于处理元件的可执行特定信息的多部分签名和该实例的上下文特定信息的多部分签名; 访问资源功能的数据库以识别与所述可执行特定信息相对应的静态资源功能以及与所述上下文特定信息相对应的与上下文相关的资源功能; 结合静态资源功能和上下文相关资源功能,形成实例的复合资源功能; 以及将所述资源功能应用于所述至少一个指定的性能度量和所述处理能力以生成所述至少一个指定的性能度量的所述资源功能估计,以供所述实例处理。

    IDENTIFYING INCONSISTENCIES IN OBJECT SIMILARITIES FROM MULTIPLE INFORMATION SOURCES
    4.
    发明申请
    IDENTIFYING INCONSISTENCIES IN OBJECT SIMILARITIES FROM MULTIPLE INFORMATION SOURCES 有权
    识别来自多个信息来源的对象类似中的不符合

    公开(公告)号:US20130151543A1

    公开(公告)日:2013-06-13

    申请号:US13316178

    申请日:2011-12-09

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30598 G11B27/32

    摘要: A horizontal anomaly detection method includes receiving at plurality of objects described in a plurality of information sources, wherein each individual information source captures a plurality of similarity relationships between the objects, combining the information sources to determine a similarity matrix whose entries represent quantitative scores of similarity between pairs of the objects, and identifying at least one horizontal anomaly of the objects within the similarity matrix, wherein the horizontal anomalies are anomalous relationships across the plurality of information sources.

    摘要翻译: 水平异常检测方法包括在多个信息源中描述的多个对象处接收,其中每个单独的信息源捕获对象之间的多个相似关系,组合信息源以确定其条目表示相似度的定量分数的相似性矩阵 在所述对象之间,并且识别所述相似性矩阵内的对象的至少一个水平异常,其中所述水平异常是所述多个信息源之间的异常关系。

    Identifying inconsistencies in object similarities from multiple information sources
    5.
    发明授权
    Identifying inconsistencies in object similarities from multiple information sources 有权
    识别来自多个信息源的对象相似性的不一致

    公开(公告)号:US08572107B2

    公开(公告)日:2013-10-29

    申请号:US13316178

    申请日:2011-12-09

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30598 G11B27/32

    摘要: A horizontal anomaly detection method includes receiving at plurality of objects described in a plurality of information sources, wherein each individual information source captures a plurality of similarity relationships between the objects, combining the information sources to determine a similarity matrix whose entries represent quantitative scores of similarity between pairs of the objects, and identifying at least one horizontal anomaly of the objects within the similarity matrix, wherein the horizontal anomalies are anomalous relationships across the plurality of information sources.

    摘要翻译: 水平异常检测方法包括在多个信息源中描述的多个对象处接收,其中每个单独的信息源捕获对象之间的多个相似关系,组合信息源以确定其条目表示相似度的定量分数的相似性矩阵 在所述对象之间,并且识别所述相似性矩阵内的对象的至少一个水平异常,其中所述水平异常是所述多个信息源之间的异常关系。

    MICROFLUIDIC VALVE MODULE AND SYSTEM FOR IMPLEMENTATION
    6.
    发明申请
    MICROFLUIDIC VALVE MODULE AND SYSTEM FOR IMPLEMENTATION 审中-公开
    微流控阀模块和实现系统

    公开(公告)号:US20140346378A1

    公开(公告)日:2014-11-27

    申请号:US13977480

    申请日:2011-12-21

    IPC分类号: F16K99/00

    摘要: An improved microfluidic system with an improved microfluidic valve module is disclosed. The microfluidic system includes a microfluidic chip and one or more valve modules. The microfluidic chip has microfluidic channels and one or more cavities formed in the chip, each of the one or more cavities designed to receive one of the one or more valve modules. Each of the one or more valve modules includes a first layer, a control layer and one or more second layers. The first layer includes a deformable material. The control layer has a microfluidic control chamber formed in a portion of it. The control layer is also located adjoining the first layer and the deformable material of the first layer forms a deformable surface of the control chamber. The one or more second layers include an input microfluidic channel and an output microfluidic channel. The input microfluidic channel and the output microfluidic channel are fluidically coupled to the microfluidic control chamber, and fluid flow through the input microfluidic channel, the microfluidic control chamber and the output microfluidic channel is controlled in response to a force deforming the deformable material of the first layer at least a predetermined amount.

    摘要翻译: 公开了具有改进的微流体阀模块的改进的微流体系统。 微流体系统包括微流体芯片和一个或多个阀模块。 微流体芯片具有微流体通道和在芯片中形成的一个或多个空腔,所述一个或多个空腔中的每一个被设计成容纳一个或多个阀模块中的一个。 一个或多个阀模块中的每一个包括第一层,控制层和一个或多个第二层。 第一层包括可变形材料。 控制层具有形成在其一部分中的微流控制室。 控制层也邻接第一层并且第一层的可变形材料形成控制室的可变形表面。 一个或多个第二层包括输入微流体通道和输出微流体通道。 输入微流体通道和输出微流体通道流体耦合到微流控制室,并且通过输入微流体通道,微流控制室和输出微流体通道的流体流动被响应于使第一 层至少预定量。

    System and method for scalable cost-sensitive learning
    8.
    发明授权
    System and method for scalable cost-sensitive learning 有权
    可扩展成本敏感学习的系统和方法

    公开(公告)号:US07904397B2

    公开(公告)日:2011-03-08

    申请号:US12690502

    申请日:2010-01-20

    IPC分类号: G06F15/18 G06N3/00 G06N3/12

    CPC分类号: G06N99/005

    摘要: A method (and structure) for processing an inductive learning model for a dataset of examples, includes dividing the dataset of examples into a plurality of subsets of data and generating, using a processor on a computer, a learning model using examples of a first subset of data of the plurality of subsets of data. The learning model being generated for the first subset comprises an initial stage of an evolving aggregate learning model (ensemble model) for an entirety of the dataset, the ensemble model thereby providing an evolving estimated learning model for the entirety of the dataset if all the subsets were to be processed. The generating of the learning model using data from a subset includes calculating a value for at least one parameter that provides an objective indication of an adequacy of a current stage of the ensemble model.

    摘要翻译: 一种用于处理实例的数据集的感应学习模型的方法(和结构),包括将示例的数据集划分成多个数据子集,并使用计算机上的处理器生成使用第一子集的示例的学习模型 的多个数据子集的数据。 为第一子集生成的学习模型包括用于整个数据集的演进聚合学习模型(集合模型)的初始阶段,从而为整个数据集提供演进的估计学习模型,如果所有子集 被处理。 使用来自子集的数据生成学习模型包括计算至少一个参数的值,所述参数提供对所述集合模型的当前阶段的充分性的客观指示。

    System and method for sequence-based subspace pattern clustering
    9.
    发明授权
    System and method for sequence-based subspace pattern clustering 失效
    基于序列的子空间模式聚类的系统和方法

    公开(公告)号:US07565346B2

    公开(公告)日:2009-07-21

    申请号:US10858541

    申请日:2004-05-31

    IPC分类号: G06F17/30

    CPC分类号: G06K9/6215 Y10S707/99936

    摘要: Unlike traditional clustering methods that focus on grouping objects with similar values on a set of dimensions, clustering by pattern similarity finds objects that exhibit a coherent pattern of rise and fall in subspaces. Pattern-based clustering extends the concept of traditional clustering and benefits a wide range of applications, including e-Commerce target marketing, bioinformatics (large scale scientific data analysis), and automatic computing (web usage analysis), etc. However, state-of-the-art pattern-based clustering methods (e.g., the pCluster algorithm) can only handle datasets of thousands of records, which makes them inappropriate for many real-life applications. Furthermore, besides the huge data volume, many data sets are also characterized by their sequentiality, for instance, customer purchase records and network event logs are usually modeled as data sequences. Hence, it becomes important to enable pattern-based clustering methods i) to handle large datasets, and ii) to discover pattern similarity embedded in data sequences. There is presented herein a novel method that offers this capability.

    摘要翻译: 与传统的集群方法不同,传统的集群方法集中在对一组维度上具有类似值的对象进行分组,通过模式相似性进行聚类可以找到在子空间中呈现一致的上升和下降模式的对象。 基于模式的群集扩展了传统群集的概念,受益于广泛的应用,包括电子商务目标营销,生物信息学(大规模科学数据分析)和自动计算(Web使用分析)等。然而,状态 基于图案的聚类方法(例如,pCluster算法)只能处理数千条记录的数据集,这使得它们不适合许多现实生活中的应用。 此外,除了巨大的数据量之外,许多数据集的特征还在于它们的顺序性,例如,客户购买记录和网络事件日志通常被建模为数据序列。 因此,重要的是启用基于图案的聚类方法i)处理大数据集,以及ii)发现嵌入在数据序列中的模式相似性。 这里提供了一种提供这种能力的新颖方法。

    Heating apparatus with enhanced thermal uniformity and method for making thereof
    10.
    发明申请
    Heating apparatus with enhanced thermal uniformity and method for making thereof 有权
    具有增强的热均匀性的加热装置及其制造方法

    公开(公告)号:US20080066676A1

    公开(公告)日:2008-03-20

    申请号:US11549968

    申请日:2006-10-16

    IPC分类号: C23C16/00

    CPC分类号: C23C16/4586 H01L21/67103

    摘要: A heating apparatus for regulating/controlling the surface temperature of a substrate is provided. At least a thermal pyrolytic graphite (TPG) layer is embedded in the heater to diffuse the temperature difference of the various components in the heating apparatus and provide temporal and spatial control of the surface temperature of the substrate, for a relatively uniform substrate temperature with the difference between the maximum and minimum temperature points on the substrate of less than 10° C.

    摘要翻译: 提供一种用于调节/控制基板的表面温度的加热装置。 至少一个热解石墨(TPG)层嵌入在加热器中以扩散加热装置中的各种组分的温度差,并提供衬底的表面温度的时间和空间控制,对于相对均匀的衬底温度, 基板上最大和最小温度点之间的差值小于10°C