Classification of stream-based data using machine learning
    2.
    发明授权
    Classification of stream-based data using machine learning 有权
    使用机器学习分析基于流的数据

    公开(公告)号:US09122995B2

    公开(公告)日:2015-09-01

    申请号:US13047804

    申请日:2011-03-15

    IPC分类号: G06N99/00

    CPC分类号: G06N99/005

    摘要: The described implementations relate to data classification. One implementation includes identifying one or more likely classifications for an incoming data item using an algorithm. The implementation can also include providing the one or more identified classifications to a user. A selection of an individual identified classification for the incoming data item can be received from the user. The algorithm can be refined to reflect the selection by the user.

    摘要翻译: 所描述的实现涉及数据分类。 一个实现包括使用算法识别输入数据项的一个或多个可能的分类。 该实现还可以包括向用户提供一个或多个所识别的分类。 可以从用户接收对输入数据项目的单独识别的分类的选择。 该算法可以被细化以反映用户的选择。

    NON-LINGUISTIC SIGNAL DETECTION AND FEEDBACK
    3.
    发明申请
    NON-LINGUISTIC SIGNAL DETECTION AND FEEDBACK 有权
    非线性信号检测和反馈

    公开(公告)号:US20110292162A1

    公开(公告)日:2011-12-01

    申请号:US12789142

    申请日:2010-05-27

    IPC分类号: H04N7/14

    CPC分类号: H04N7/15 H04N7/147

    摘要: Non-linguistic signal information relating to one or more participants to an interaction may be determined using communication data received from the one or more participants. Feedback can be provided based on the determined non-linguistic signals. The participants may be given an opportunity to opt in to having their non-linguistic signal information collected, and may be provided complete control over how their information is shared or used.

    摘要翻译: 可以使用从一个或多个参与者接收的通信数据来确定与交互的一个或多个参与者有关的非语言信号信息。 可以基于确定的非语言信号提供反馈。 参与者可能有机会选择收集其非语言信号信息,并且可以完全控制他们的信息如何共享或使用。

    Interactive Optimization of the Behavior of a System
    4.
    发明申请
    Interactive Optimization of the Behavior of a System 有权
    交互式优化系统的行为

    公开(公告)号:US20110251980A1

    公开(公告)日:2011-10-13

    申请号:US12756183

    申请日:2010-04-08

    IPC分类号: G06F15/18 G06N5/02 G06F1/24

    CPC分类号: G06N99/005

    摘要: An interactive tool is described for modifying the behavior of a system, such as, but not limited to, the behavior of a classification system. The tool uses an interface mechanism to present a current global state of the system. The tool accepts one or more refinements to this global state, e.g., by accepting individual changes to parameter settings that are presented by the interface mechanism. Based on this input, the tool computes and displays the global implications of the updated parameter settings. The process of iterating over one or more cycles of user updates, followed by computation and display of the implications of the attempted refinements, has the effect of advancing the system towards a global state that exhibits desirable behavior.

    摘要翻译: 描述了用于修改系统的行为的交互式工具,例如但不限于分类系统的行为。 该工具使用接口机制来呈现系统的当前全局状态。 该工具接受对该全局状态的一个或多个改进,例如通过接受由接口机制呈现的参数设置的单独改变。 基于此输入,该工具计算并显示更新参数设置的全局含义。 迭代一个或多个用户更新周期的过程,随后计算和显示尝试改进的含义,具有将系统推向呈现期望行为的全局状态的效果。

    INTERACTIVE VISUALIZATION FOR GENERATING ENSEMBLE CLASSIFIERS
    5.
    发明申请
    INTERACTIVE VISUALIZATION FOR GENERATING ENSEMBLE CLASSIFIERS 有权
    用于生成ENSEMBLE分类器的交互式可视化

    公开(公告)号:US20100241596A1

    公开(公告)日:2010-09-23

    申请号:US12408663

    申请日:2009-03-20

    IPC分类号: G06F17/00 G06F15/18 G06N5/02

    CPC分类号: G06N99/005

    摘要: A real-time visual feedback ensemble classifier generator and method for interactively generating an optimal ensemble classifier using a user interface. Embodiments of the real-time visual feedback ensemble classifier generator and method use a weight adjustment operation and a partitioning operation in the interactive generation process. In addition, the generator and method include a user interface that provides real-time visual feedback to a user so that the user can see how the weight adjustment and partitioning operation affect the overall accuracy of the ensemble classifier. Using the user interface and the interactive controls available on the user interface, a user can iteratively use one or both of the weigh adjustment operation and partitioning operation to generate an optimized ensemble classifier.

    摘要翻译: 一种实时视觉反馈综合分类器生成器和方法,用于使用用户界面交互式生成最佳集合分类器。 实时视觉反馈综合分类器发生器和方法的实施例在交互式生成过程中使用权重调整操作和分割操作。 此外,发生器和方法包括向用户提供实时视觉反馈的用户界面,使得用户可以看到权重调整和分割操作如何影响整体分类器的整体精度。 使用用户界面上的用户界面和交互式控件,用户可以迭代地使用权重调整操作和分区操作中的一个或两者来生成优化的整体分类器。

    Submerged arc flux
    6.
    发明授权
    Submerged arc flux 有权
    埋弧焊

    公开(公告)号:US07727339B2

    公开(公告)日:2010-06-01

    申请号:US11144423

    申请日:2005-06-06

    IPC分类号: B23K35/34 B23K35/24

    摘要: A highly basic particle flux for submerged arc welding that produces less than 7 ml/100 gr of diffusible hydrogen in the weld metal, which flux comprises a carbon dioxide containing compound with an effective amount of heat releasable carbon dioxide in the range of 0.5-3.5% by weight of the flux over 10% by weight of a low melting point compound and a binder.

    摘要翻译: 用于埋弧焊的高度基本的颗粒通量,其在焊缝金属中产生小于7ml / 100gr的可扩散氢,该焊剂包含含二氧化碳的化合物,其中有效量的可热释放的二氧化碳的范围为0.5-3.5 通量超过10重量%的低熔点化合物和粘合剂的重量%。

    INTERACTIVE CONCEPT LEARNING IN IMAGE SEARCH
    7.
    发明申请
    INTERACTIVE CONCEPT LEARNING IN IMAGE SEARCH 有权
    图像搜索中的交互式概念学习

    公开(公告)号:US20090154795A1

    公开(公告)日:2009-06-18

    申请号:US11954246

    申请日:2007-12-12

    IPC分类号: G06K9/62

    CPC分类号: G06F17/30247 G06K9/6215

    摘要: An interactive concept learning image search technique that allows end-users to quickly create their own rules for re-ranking images based on the image characteristics of the images. The image characteristics can include visual characteristics as well as semantic features or characteristics, or may include a combination of both. End-users can then rank or re-rank any current or future image search results according to their rule or rules. End-users provide examples of images each rule should match and examples of images the rule should reject. The technique learns the common image characteristics of the examples, and any current or future image search results can then be ranked or re-ranked according to the learned rules.

    摘要翻译: 一种交互式概念学习图像搜索技术,允许最终用户基于图像的图像特征快速创建自己的重新排序图像的规则。 图像特征可以包括视觉特征以及语义特征或特征,或者可以包括两者的组合。 然后,最终用户可以根据其规则或规则对当前或将来的图像搜索结果进行排名或重新排序。 最终用户提供每个规则应该匹配的图像的示例以及规则应该拒绝的图像的示例。 该技术学习示例的常见图像特征,然后可以根据学习的规则对任何当前或将来的图像搜索结果进行排名或重新排序。

    Submerged arc flux
    8.
    发明申请
    Submerged arc flux 有权
    埋弧焊

    公开(公告)号:US20060272746A1

    公开(公告)日:2006-12-07

    申请号:US11144423

    申请日:2005-06-06

    IPC分类号: B23K35/34

    摘要: A highly basic particle flux for submerged arc welding that produces less than 7 ml/100 gr of diffusible hydrogen in the weld metal, which flux comprises a carbon dioxide containing compound with an effective amount of heat releasable carbon dioxide in the range of 0.5-3.5% by weight of the flux over 10% by weight of a low melting point compound and a binder.

    摘要翻译: 用于埋弧焊的高度基本的颗粒通量,其在焊缝金属中产生小于7ml / 100gr的可扩散氢,该焊剂包含含二氧化碳的化合物,其中有效量的可热释放的二氧化碳的范围为0.5-3.5 通量超过10重量%的低熔点化合物和粘合剂的重量%。

    Construction of a technology library for use in an electronic design automation system that converts the technology library into non-linear, gain-based models for estimating circuit delay
    9.
    发明授权
    Construction of a technology library for use in an electronic design automation system that converts the technology library into non-linear, gain-based models for estimating circuit delay 有权
    构建用于电子设计自动化系统的技术库,将技术库转换为非线性,基于增益的模型,用于估计电路延迟

    公开(公告)号:US06789232B1

    公开(公告)日:2004-09-07

    申请号:US10192760

    申请日:2002-07-09

    IPC分类号: G06F1750

    CPC分类号: G06F17/5068

    摘要: A system and process for constructing a technology library that is suitable for use with an electronic design automation system that converts the target technology library into a scalable cell library having non-linear, gain-based delay models for estimating circuit delay. The scalable cell library can then be used by gain-based structuring and mapping processes. The library construction process places at least six discrete cells in each logic function of a basic cell set. The library construction process also places at least five discrete cells in each logic function of an extended cell set and rules out cell sizing using internal buffer circuits. Also, for each discrete cell in the complete cell set, the variance of the capacitances between different input pins of the cell is maintained to be within 10 percent. For corresponding timing arcs of discrete sizes for a particular logic function, the present invention keeps equal the ratio of the output load to input capacitance. Also, the present invention constructs a technology library that has geometrically distributed sizes of cells within each logic function. Lastly, for each discrete cell within a logic cluster, the output maximum capacitance constraint is kept linearly proportional to the average input capacitance of the discrete cell. These processes likely allow a technology library to be suitable for the generation of a scalable library which can be used for integrated circuit design and fabrications.

    摘要翻译: 一种用于构建技术库的系统和过程,该技术库适用于将目标技术库转换成具有用于估计电路延迟的非线性增益型延迟模型的可扩展单元库的电子设计自动化系统。 然后,可扩展单元库可以通过基于增益的结构化和映射过程来使用。 图书馆建设过程在基本单元格的每个逻辑功能中放置至少六个离散单元格。 库构建过程还在扩展单元组的每个逻辑功能中至少放置五个离散单元,并使用内部缓冲电路排除单元大小。 此外,对于完整单元组中的每个离散单元,单元的不同输入引脚之间的电容的方差保持在10%以内。 对于特定逻辑功能的离散尺寸的相应定时弧,本发明保持输出负载与输入电容的比值相等。 此外,本发明构造了在每个逻辑功能内具有几何分布的单元格大小的技术库。 最后,对于逻辑簇内的每个离散单元,输出最大电容约束与离散单元的平均输入电容成线性比例。 这些过程可能允许技术库适用于生成可用于集成电路设计和制造的可扩展库。

    Non-linear, gain-based modeling of circuit delay for an electronic design automation system
    10.
    发明授权
    Non-linear, gain-based modeling of circuit delay for an electronic design automation system 有权
    电子设计自动化系统的电路延迟非线性增益建模

    公开(公告)号:US06543036B1

    公开(公告)日:2003-04-01

    申请号:US09452056

    申请日:1999-11-30

    IPC分类号: G06F1750

    CPC分类号: G06F17/5022

    摘要: A non-linear, gain-based modeling of circuit delay within an electronic design automation system. The present invention provides a scalable cell model for use in early logic structuring and mapping for the design of integrated circuits. The scalable cell model includes a four dimensional delay model accepting input slew and gain and providing delay and output slew. By eliminating output loading as a requirement for delay computations, the scalable model of the present invention can effectively be used to provide accurate delay information for early logic synthesis processes, e.g., that precede technology dependent optimizations where the actual load of a cell is unknown. This scalable cell model considers: the impact of transition times on delay; complex gates having different input capacitances for different input pins; the impact of limited discrete cell sizes in the technology library; and design rules, e.g., maximum capacitance and maximum transition associated with gates. A technology library is analyzed and clustering is performed to select a cluster of cells for each cell group of a common functionality. A nominal input slew value is computed for all cells and a scaling factor is computed for each cell of each cluster. From each cluster, a four dimensional gain-based non-linear scalable cell model (look-up table) is generated. A default gain is computed for each scalable cell model and an area model and an input pin capacitance model are generated for each scalable cell model.

    摘要翻译: 电子设计自动化系统中电路延迟的非线性增益建模。 本发明提供了用于集成电路设计的早期逻辑结构和映射中的可扩展小区模型。 可扩展单元模型包括接受输入转换和增益的四维延迟模型,并提供延迟和输出转换。 通过消除输出负载作为延迟计算的要求,本发明的可缩放模型可以有效地用于为早期逻辑合成过程提供准确的延迟信息,例如,在单元的实际负载未知的技术相关优化之前。 这种可扩展的小区模型考虑:转换时间对延迟的影响; 具有不同输入引脚的不同输入电容的复门; 技术库中有限的离散小区尺寸的影响; 和设计规则,例如与门相关联的最大电容和最大转变。 分析技术库并执行集群以为共同功能的每个单元组选择一组单元格。 计算所有单元的标称输入转换值,并为每个单元的每个单元计算缩放因子。 从每个集群中,生成基于四维增益的非线性可伸缩单元模型(查找表)。 为每个可缩放单元模型计算默认增益,并为每个可缩放单元模型生成区域模型和输入引脚电容模型。