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:
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:
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:
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:
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:
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:
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:
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:
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.