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    Electrode compositions for use with analyte sensors
    4.
    发明授权
    Electrode compositions for use with analyte sensors 有权
    用于分析物传感器的电极组合物

    公开(公告)号：US08808532B2

    公开(公告)日：2014-08-19

    申请号：US13010636

    申请日：2011-01-20

    Applicant: Qingling Yang ,  Rajiv Shah ,  Xiaolong Li ,  Barry Phong Pham ,  Yiwen Li

    Inventor： Qingling Yang ,  Rajiv Shah ,  Xiaolong Li ,  Barry Phong Pham ,  Yiwen Li

    IPC: G01N27/327

    CPC classification number: C12Q1/001 ,  C12Q1/005

    Abstract: Embodiments of the invention provide amperometric analyte sensors having optimized elements such as electrodes formed from sputtered platinum compositions as well as layers of material selected to optimize the characteristics of a wide variety of sensor elements and sensors. While embodiments of the innovation can be used in a variety of contexts, typical embodiments of the invention include glucose sensors used in the management of diabetes.

    Abstract translation: 本发明的实施例提供具有优化元件的电流分析传感器，例如由溅射的铂组合物形成的电极以及被选择用于优化各种传感器元件和传感器的特性的材料层。 尽管可以在多种情况下使用创新的实施例，但是本发明的典型实施例包括用于糖尿病管理的葡萄糖传感器。

    Bootstrap and adapt a document search engine
    5.
    发明授权
    Bootstrap and adapt a document search engine 有权
    引导和调整文档搜索引擎

    公开(公告)号：US08527534B2

    公开(公告)日：2013-09-03

    申请号：US12726358

    申请日：2010-03-18

    Applicant: Kuansan Wang ,  Bo-June Hsu ,  Xiaolong Li

    Inventor： Kuansan Wang ,  Bo-June Hsu ,  Xiaolong Li

    IPC: G06F17/30

    CPC classification number: G06F17/30654 ,  G06F17/30731 ,  G06F17/30976

    Abstract: Architecture that employs a modeling technique based on language modeling to estimate a probability of a document matching the user need as expressed in the query. The modeling technique is based on the data mining results that various portions of a document (e.g., body, title, URL, anchor text, user queries) use different styles of human languages. Thus, the results based on a language can be adapted individually to match the language of query. Since the approach is based on adaptation, the framework also provides a natural means to progressively revise the model as user data are collected. Different styles of languages in a document can be recognized and adapted individually. Background language models are also employed that offer a fallback approach in case the document has incomplete fields of data, and can utilize topical or semantic hierarchy of the knowledge domain.

    Abstract translation: 采用基于语言建模的建模技术的架构来估计在查询中表达的与用户匹配的文档的概率。 建模技术基于数据挖掘结果，文档的各个部分（例如，主体，标题，URL，锚文本，用户查询）使用不同风格的人类语言。 因此，基于语言的结果可以单独调整以匹配查询语言。 由于该方法是基于适应性的，所以该框架还提供了一种在收集用户数据时逐步修改模型的自然方法。 文档中不同风格的语言可以单独识别和修改。 还使用背景语言模型，在文档具有不完整的数据领域的情况下提供回退方法，并且可以利用知识领域的局部或语义层次结构。

    Routing device
    6.
    发明授权
    Routing device 失效
    路由设备

    公开(公告)号：US07975617B2

    公开(公告)日：2011-07-12

    申请号：US12786432

    申请日：2010-05-25

    Applicant: Xiaolong Li

    Inventor： Xiaolong Li

    IPC: E01B25/00

    CPC classification number: E01B25/28 ,  B60F1/00 ,  B60F1/043 ,  B61D15/00 ,  B61K5/04

    Abstract: A routing device, including a sliding device, a rotating shaft, a pair of route rails, a pair of rams, and a pillow, wherein the route rail is disposed in the front of a railway track, the route rails are disposed on the rams, the rotating shaft is disposed at one end of the ram in the vicinity of the railway track, and connected to the pillow, the sliding device is disposed between the ram and the pillow, and the ram operates to laterally slide on the pillow. The invention features simple structure and low investigation cost, occupies small space, is not only applicable for route of normal road and rail vehicles, but also for that of long multi-axis vehicles composed of tractors and trailers, or vehicle trains, and thus enabling the road and rail vehicles to be widely used and saving power.

    Abstract translation: 一种路线装置，包括滑动装置，旋转轴，一对路径轨道，一对柱塞和枕头，其中，所述路线轨道设置在铁路轨道的前部，所述路线轨道设置在所述公羊 旋转轴设置在铁路轨道附近的冲头的一端，并且与枕头相连，滑动装置设置在冲头和枕头之间，并且压头在枕头上横向滑动。 本发明结构简单，调查成本低，占地面积小，不仅适用于普通公路和铁路车辆的路线，而且适用于拖拉机，拖车，车辆列车等多长时间的长途车辆，从而实现 道路和轨道车辆被广泛使用和节约电力。

    Automatic reading tutoring
    7.
    发明申请
    Automatic reading tutoring 有权
    自动阅读辅导

    公开(公告)号：US20090070112A1

    公开(公告)日：2009-03-12

    申请号：US11900274

    申请日：2007-09-11

    Applicant: Xiaolong Li ,  Li Deng ,  Yun-Cheng Ju ,  Alex Acero

    Inventor： Xiaolong Li ,  Li Deng ,  Yun-Cheng Ju ,  Alex Acero

    IPC: G10L15/18

    CPC classification number: G10L15/18 ,  G09B17/003 ,  G10L15/183

    Abstract: A method of providing automatic reading tutoring is disclosed. The method includes retrieving a textual indication of a story from a data store and creating a language model including constructing a target context free grammar indicative of a first portion of the story. A first acoustic input is received and a speech recognition engine is employed to recognize the first acoustic input. An output of the speech recognition engine is compared to the language model and a signal indicative of whether the output of the speech recognition matches at least a portion of the target context free grammar is provided.

    Abstract translation: 公开了提供自动阅读辅导的方法。 该方法包括从数据存储中检索故事的文本指示并创建包括构建指示故事的第一部分的目标上下文自由语法的语言模型。 接收到第一声输入，并且采用语音识别引擎来识别第一声输入。 将语音识别引擎的输出与语言模型进行比较，并且提供指示语音识别的输出是否与目标语境自由语法的至少一部分匹配的信号。

    Layered enzyme compositions for use with analyte sensors
    9.
    发明授权
    Layered enzyme compositions for use with analyte sensors 有权
    用于分析物传感器的分层酶组合物

    公开(公告)号：US08608921B2

    公开(公告)日：2013-12-17

    申请号：US13010640

    申请日：2011-01-20

    Applicant: Xiaolong Li ,  Rajiv Shah ,  Qingling Yang ,  Yiwen Li ,  Barry Phong Pham

    Inventor： Xiaolong Li ,  Rajiv Shah ,  Qingling Yang ,  Yiwen Li ,  Barry Phong Pham

    IPC: G01N27/327 ,  G01N27/416

    CPC classification number: C12Q1/00 ,  C12Q1/005 ,  C12Q1/006

    Abstract: Embodiments of the invention provide amperometric analyte sensors having optimized elements such as electrodes formed from sputtered platinum compositions as well as layers of material selected to optimize the characteristics of a wide variety of sensor elements and sensors. While embodiments of the innovation can be used in a variety of contexts, typical embodiments of the invention include glucose sensors used in the management of diabetes.

    Abstract translation: 本发明的实施例提供具有优化元件的电流分析传感器，例如由溅射的铂组合物形成的电极以及被选择用于优化各种传感器元件和传感器的特性的材料层。 尽管可以在多种情况下使用创新的实施例，但是本发明的典型实施例包括用于糖尿病管理的葡萄糖传感器。

    Automatic reading tutoring with parallel polarized language modeling
    10.
    发明授权
    Automatic reading tutoring with parallel polarized language modeling 有权
    使用平行极化语言建模的自动阅读辅导

    公开(公告)号：US08433576B2

    公开(公告)日：2013-04-30

    申请号：US11655702

    申请日：2007-01-19

    Applicant: Xiaolong Li ,  Yun-Cheng Ju ,  Li Deng ,  Alejandro Acero

    Inventor： Xiaolong Li ,  Yun-Cheng Ju ,  Li Deng ,  Alejandro Acero

    IPC: G10L15/22

    CPC classification number: G06F17/271 ,  G09B17/003 ,  G10L15/197 ,  G10L2015/221

    Abstract: A novel system for automatic reading tutoring provides effective error detection and reduced false alarms combined with low processing time burdens and response times short enough to maintain a natural, engaging flow of interaction. According to one illustrative embodiment, an automatic reading tutoring method includes displaying a text output and receiving an acoustic input. The acoustic input is modeled with a domain-specific target language model specific to the text output, and with a general-domain garbage language model, both of which may be efficiently constructed as context-free grammars. The domain-specific target language model may be built dynamically or “on-the-fly” based on the currently displayed text (e.g. the story to be read by the user), while the general-domain garbage language model is shared among all different text outputs. User-perceptible tutoring feedback is provided based on the target language model and the garbage language model.

    Abstract translation: 用于自动阅读辅导的新颖系统提供了有效的错误检测和减少的假警报以及较短的处理时间负担和响应时间足够短以保持自然的，互动的互动流。 根据一个说明性实施例，自动阅读辅导方法包括显示文本输出并接收声输入。 声输入是用专门针对文本输出的领域特定的目标语言模型建立的，并且具有通用域垃圾语言模型，这两种语言模型都可以被有效地构建为无上下文的语法。 可以基于当前显示的文本（例如，用户要阅读的故事）动态地或“即时”地构建特定领域的目标语言模型，而一般域垃圾语言模型在所有不同的方式之间共享 文本输出。 基于目标语言模型和垃圾语言模型提供了用户可感知的辅导反馈。

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