Non-vacuum method for fabrication of a photovoltaic absorber layer
    1.
    发明授权
    Non-vacuum method for fabrication of a photovoltaic absorber layer 失效
    用于制造光伏吸收层的非真空方法

    公开(公告)号:US08748216B2

    公开(公告)日:2014-06-10

    申请号:US13198744

    申请日:2011-08-05

    IPC分类号: H01L31/18 H01L31/032

    摘要: The present invention provides a non-vacuum method of depositing a photovoltaic absorber layer based on electrophoretic deposition of a mixture of nanoparticles with a controlled atomic ratio between the elements. The nanoparticles are first dispersed in a liquid medium to form a colloidal suspension and then electrophoretically deposited onto a substrate to form a thin film photovoltaic absorber layer. The absorber layer may be subjected to optional post-deposition treatments for photovoltaic absorption.

    摘要翻译: 本发明提供了一种非真空方法,其基于在元件之间具有受控原子比的纳米颗粒的混合物的电泳沉积来沉积光伏吸收层。 首先将纳米颗粒分散在液体介质中以形成胶体悬浮液,然后电泳沉积到基底上以形成薄膜光伏吸收层。 可以对吸收层进行用于光伏吸收的任选的后沉积处理。

    NON-VACUUM METHOD FOR FABRICATION OF A PHOTOVOLTAIC ABSORBER LAYER
    2.
    发明申请
    NON-VACUUM METHOD FOR FABRICATION OF A PHOTOVOLTAIC ABSORBER LAYER 失效
    用于制造光伏吸收层的非真空方法

    公开(公告)号:US20120098032A1

    公开(公告)日:2012-04-26

    申请号:US13198744

    申请日:2011-08-05

    IPC分类号: H01L31/18 H01L31/032

    摘要: The present invention provides a non-vacuum method of depositing a photovoltaic absorber layer based on electrophoretic deposition of a mixture of nanoparticles with a controlled atomic ratio between the elements. The nanoparticles are first dispersed in a liquid medium to form a colloidal suspension and then electrophoretically deposited onto a substrate to form a thin film photovoltaic absorber layer. The absorber layer may be subjected to optional post-deposition treatments for photovoltaic absorption.

    摘要翻译: 本发明提供了一种非真空方法,其基于在元件之间具有受控原子比的纳米颗粒的混合物的电泳沉积来沉积光伏吸收层。 首先将纳米颗粒分散在液体介质中以形成胶体悬浮液,然后电泳沉积到基底上以形成薄膜光伏吸收层。 可以对吸收层进行用于光伏吸收的任选的后沉积处理。

    Non-vacuum method for fabrication of a photovoltaic absorber layer
    4.
    发明授权
    Non-vacuum method for fabrication of a photovoltaic absorber layer 失效
    用于制造光伏吸收层的非真空方法

    公开(公告)号:US08409906B2

    公开(公告)日:2013-04-02

    申请号:US12910929

    申请日:2010-10-25

    IPC分类号: H01L21/00

    摘要: The present invention provides a non-vacuum method of depositing a photovoltaic absorber layer based on electrophoretic deposition of a mixture of nanoparticles with a controlled atomic ratio between the elements. The nanoparticles are first dispersed in a liquid medium to form a colloidal suspension and then electrophoretically deposited onto a substrate to form a thin film photovoltaic absorber layer. The absorber layer may be subjected to optional post-deposition treatments for photovoltaic absorption.

    摘要翻译: 本发明提供了一种非真空方法,其基于在元件之间具有受控原子比的纳米颗粒的混合物的电泳沉积来沉积光伏吸收层。 首先将纳米颗粒分散在液体介质中以形成胶体悬浮液,然后电泳沉积到基底上以形成薄膜光伏吸收层。 可以对吸收层进行用于光伏吸收的任选的后沉积处理。

    SCALABLE TRAFFIC CLASSIFIER AND CLASSIFIER TRAINING SYSTEM
    5.
    发明申请
    SCALABLE TRAFFIC CLASSIFIER AND CLASSIFIER TRAINING SYSTEM 有权
    可扩展的交通分类器和分类器培训系统

    公开(公告)号:US20130013542A1

    公开(公告)日:2013-01-10

    申请号:US13620668

    申请日:2012-09-14

    IPC分类号: G06F15/18 G06N5/02

    CPC分类号: G06N99/005

    摘要: A traffic classifier has a plurality of binary classifiers, each associated with one of a plurality of calibrators. Each calibrator trained to translate an output score of the associated binary classifier into an estimated class probability value using a fitted logistic curve, each estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. The classifier training system configured to generate a training data based on network information gained using flow and packet sampling methods. In some embodiments, the classifier training system configured to generate reduced training data sets, one for each traffic class, reducing the training data related to traffic not associated with the traffic class.

    摘要翻译: 流量分类器具有多个二进制分类器,每个二进制分类器与多个校准器之一相关联。 每个校准器被训练成使用拟合的逻辑曲线将相关联的二进制分类器的输出得分转换成估计的类概率值,每个估计的类概率值指示输出得分所基于的分组流的概率属于相关联的流量类别 与校准器相关联的二进制分类器。 分类器训练系统被配置为基于使用流和分组采样方法获得的网络信息生成训练数据。 在一些实施例中,分类器训练系统被配置为生成减少的训练数据集,每个业务类别一个,减少与业务类别不相关的业务相关的训练数据。

    Method and apparatus for encoding a mesh model, encoded mesh model, and method and apparatus for decoding a mesh model
    6.
    发明授权
    Method and apparatus for encoding a mesh model, encoded mesh model, and method and apparatus for decoding a mesh model 有权
    用于编码网格模型,编码网格模型以及用于解码网格模型的方法和装置的方法和装置

    公开(公告)号:US08949092B2

    公开(公告)日:2015-02-03

    申请号:US13501662

    申请日:2009-10-15

    摘要: For most large 3D engineering models, the instance positions of repeating instances of connected components show significant multiple spatial aggregation. The invention uses several KD-trees, each for one cluster of points which are spatially aggregated. The multiple KD-trees generate a relatively short data stream, and thus improve the total compression ratio. A method for encoding points of a 3D mesh model comprises steps of determining that the mesh model comprises repeating instances of a connected component, and determining for each repeating instance at least one reference point, clustering the reference points of the repeating instances into one or more clusters, and encoding the clustered reference points using KD-tree coding, wherein for each cluster a separate KD-tree is generated.

    摘要翻译: 对于大多数大型3D工程模型,连接组件的重复实例的实例位置显示出显着的多个空间聚合。 本发明使用几个KD树,每个KD树针对空间聚集的一个点簇。 多个KD树生成相对较短的数据流,从而提高总压缩比。 用于对3D网格模型的点进行编码的方法包括以下步骤:确定所述网格模型包括连续分量的重复实例,以及针对每个重复实例确定至少一个参考点,将所述重复实例的参考点聚类成一个或多个 群集,并使用KD树编码对聚类参考点进行编码,其中对于每个簇,生成单独的KD树。

    METHOD AND APPARATUS FOR CLASSIFYING APPLICATIONS USING THE COLLECTIVE PROPERTIES OF NETWORK TRAFFIC
    8.
    发明申请
    METHOD AND APPARATUS FOR CLASSIFYING APPLICATIONS USING THE COLLECTIVE PROPERTIES OF NETWORK TRAFFIC 有权
    使用网络交通的集合性质分类应用的方法和装置

    公开(公告)号:US20120047096A1

    公开(公告)日:2012-02-23

    申请号:US12858303

    申请日:2010-08-17

    IPC分类号: G06F15/18 G06N3/08

    摘要: In one embodiment, the present disclosure is a method and apparatus for classifying applications using the collective properties of network traffic. In one embodiment, a method for classifying traffic in a communication network includes receiving a traffic activity graph, the traffic activity graph comprising a plurality of nodes interconnected by a plurality of edges, where each of the nodes represents an endpoint associated with the communication network and each of the edges represents traffic between a corresponding pair of the nodes, generating an initial set of inferences as to an application class associated with each of the edges, based on at least one measured statistic related to at least one traffic flow in the communication network, and refining the initial set of inferences based on a spatial distribution of the traffic flows, to produce a final traffic activity graph.

    摘要翻译: 在一个实施例中,本公开是用于使用网络业务的集合属性对应用进行分类的方法和装置。 在一个实施例中,用于对通信网络中的业务进行分类的方法包括接收业务活动图,所述业务活动图包括由多个边缘互连的多个节点,其中每个节点表示与所述通信网络相关联的端点, 每个边缘表示对应的一对节点之间的流量,基于与通信网络中的至少一个业务流相关的至少一个测量的统计量,生成关于与每个边缘相关联的应用类别的初始推断集合 ,并且基于业务流的空间分布来优化初始推理集合,以产生最终业务活动图。

    Scalable traffic classifier and classifier training system
    9.
    发明授权
    Scalable traffic classifier and classifier training system 有权
    可扩展流量分类器和分类器训练系统

    公开(公告)号:US09349102B2

    公开(公告)日:2016-05-24

    申请号:US13620668

    申请日:2012-09-14

    IPC分类号: G06N99/00

    CPC分类号: G06N99/005

    摘要: A traffic classifier has a plurality of binary classifiers, each associated with one of a plurality of calibrators. Each calibrator trained to translate an output score of the associated binary classifier into an estimated class probability value using a fitted logistic curve, each estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. The classifier training system configured to generate a training data based on network information gained using flow and packet sampling methods. In some embodiments, the classifier training system configured to generate reduced training data sets, one for each traffic class, reducing the training data related to traffic not associated with the traffic class.

    摘要翻译: 流量分类器具有多个二进制分类器,每个二进制分类器与多个校准器之一相关联。 每个校准器被训练成使用拟合的逻辑曲线将相关联的二进制分类器的输出得分转换成估计的类概率值,每个估计的类概率值指示输出得分所基于的分组流的概率属于相关联的流量类别 与校准器相关联的二进制分类器。 分类器训练系统被配置为基于使用流和分组采样方法获得的网络信息生成训练数据。 在一些实施例中,分类器训练系统被配置为生成减少的训练数据集,每个业务类别一个,减少与业务类别不相关的业务相关的训练数据。

    Method and apparatus for classifying applications using the collective properties of network traffic in a traffic activity graph
    10.
    发明授权
    Method and apparatus for classifying applications using the collective properties of network traffic in a traffic activity graph 有权
    使用交通活动图中网络流量的集体属性对应用进行分类的方法和装置

    公开(公告)号:US08935188B2

    公开(公告)日:2015-01-13

    申请号:US12858303

    申请日:2010-08-17

    摘要: In one embodiment, the present disclosure is a method and apparatus for classifying applications using the collective properties of network traffic. In one embodiment, a method for classifying traffic in a communication network includes receiving a traffic activity graph, the traffic activity graph comprising a plurality of nodes interconnected by a plurality of edges, where each of the nodes represents an endpoint associated with the communication network and each of the edges represents traffic between a corresponding pair of the nodes, generating an initial set of inferences as to an application class associated with each of the edges, based on at least one measured statistic related to at least one traffic flow in the communication network, and refining the initial set of inferences based on a spatial distribution of the traffic flows, to produce a final traffic activity graph.

    摘要翻译: 在一个实施例中,本公开是用于使用网络业务的集合属性对应用进行分类的方法和装置。 在一个实施例中,用于对通信网络中的业务进行分类的方法包括接收业务活动图,所述业务活动图包括由多个边缘互连的多个节点,其中每个节点表示与所述通信网络相关联的端点, 每个边缘表示对应的一对节点之间的流量,基于与通信网络中的至少一个业务流相关的至少一个测量的统计量,生成关于与每个边缘相关联的应用类别的初始推断集合 ,并且基于业务流的空间分布来优化初始推理集合,以产生最终业务活动图。