Abstract: A network device with decoupled packet and cell queueing is provided. The network device includes a traffic manager configured to obtain the one or more packets. The traffic manager further includes a packet storage configured to store one or more pointers associated with a packet of the one or more packets, the one or more pointers comprising a first type of pointer and a second type of pointer, and a cell storage configured to store cell control information of at least part of the one or more cells of the packet, wherein the cell control information includes a respective first type of pointer for each of the at least part of the one or more cells. The traffic manager further includes admission control logic configured to perform an admission check of the one or more packets without the cell control information of the one or more packets.

Abstract: The Erasable Barcode prevents the sale of products by invalidating the barcode. The invalidation can be based on shelf life, or improper temperature maintenance. The invalidation is also visible to humans so that the consumer knows if the exposure occurs after purchase. Activation brings liquid from the first reservoir in contact with the migration medium. The liquid progressively produces a change in color over time in the migration medium. When the liquid has crossed the migration medium, it will come in contact with the absorptive medium. The absorptive medium will then rapidly change color. The absorptive layer is the substrate for a machine readable barcode such that the color change renders the barcode unreadable.

Abstract: The Erasable Barcode prevents the sale of products by invalidating the barcode. The invalidation can be based on shelf life, or improper temperature maintenance. The invalidation is also visible to humans so that the consumer knows if the exposure occurs after purchase. Activation brings liquid from the first reservoir in contact with the migration medium. The liquid progressively produces a change in color over time in the migration medium. When the liquid has crossed the migration medium, it will come in contact with the absorptive medium. The absorptive medium will then rapidly change color.

Abstract: The Erasable Barcode prevents the sale of products by invalidating the barcode. The invalidation can be based on shelf life, or improper temperature maintenance. The invalidation is also visible to humans so that the consumer knows if the exposure occurs after purchase. Activation brings liquid from the first reservoir in contact with the migration medium. The liquid progressively produces a change in color over time in the migration medium. When the liquid has crossed the migration medium, it will come in contact with the absorptive medium. The absorptive medium will then rapidly change color.

Abstract: A method of training a document analysis system to extract data from documents is provided. The method includes: automatically analyzing images and text features extracted from a document to associate the document with a corresponding document category; comparing the extracted text features with a set of text features associated with corresponding category of the document, in which the set of text features includes a set of characters, words, and phrases; if the extracted features are found to consist of the characters, words, and phrases belonging to the set of text features associated with the corresponding document category, storing the extracted text features as the data contained in the corresponding document; and, if the extracted text features are found to include at least one text feature that does not belong to the set of text features associated with the corresponding document category, submitting the unrecognized text features to a training phase.

Abstract: A method of automatically extracting data from an electronic document containing a plurality of layout features through progressive refinement is provided. The method includes: analyzing each document to automatically extract images and text features wherein each document includes at least two features that are related to each other, and wherein said analyzing compares extracted features with a first search space of candidate features to try and recognize the extracted features; if one of the at least two related features is not recognized and at least one feature is recognized, selecting a second search space of candidate features in response thereto and in response to predefined rules about the relationship between the two features; and comparing the unrecognized feature with said selected second search space.

Abstract: A method of controlling a scanner to improve automatic recognition and classification of scanned physical documents for a document analysis system, which receives and processes jobs containing at least one electronic document from a plurality of users to automatically recognize and classify the job documents into document categories, is disclosed. The method comprises, using a scan control system, obtaining the capability of, and existing scanner settings for, the scanner upon receiving a command to initiate scanning of physical documents; saving the existing scanner settings of the scanner; automatically commanding the scanner to use new scanner settings, wherein the new scanner settings are selected in accordance with the capability of the recognition system; commanding the scanner to begin scanning operation with the new scanner settings; and automatically resetting the scanner settings of the scanner back to the saved existing scanner settings upon completing of the scanning operation.

Abstract: A method in a document analysis system automatically extracts image and text features from each received electronic document and compares the extracted features with feature sets associated with each category of document to determine whether the document is recognizable as belonging to a document category. If an electronic document is recognized as belonging to one of the document categories, the method classifies the electronic document as belonging to that document category. If, however, an electronic document is unrecognized, the method submits the unrecognized document to a learning phase, in which the unrecognized document is presented to a human trainer for manual classification of the unrecognized electronic document into a document category, and automatically modifies at least one of the features and the weights of the feature set of the document category corresponding to the manually-classified electronic document using the automatically extracted features of the manually-classified document.

Abstract: A method of training a document analysis system that automatically extracts image and text features from each received electronic document and compares the extracted features with feature sets associated with each document category is provided. If an electronic document is recognized as belonging to one of the document categories with predetermined confidence, the method classifies the electronic document as being of that one document category. If an electronic document is not recognized as belonging to one of the document categories with predetermined confidence, however, the method submits the unrecognized document to a training phase in which the document is recognized as belonging to a document category and automatically modifies at least one of the features and the weights of the features of the feature set for the document category for the now-recognized document.

Abstract: A document analysis system that automatically classifies documents by recognizing in each document distinctive features comprises a document acquisition system, a document recognition training system, a document classification system, a document recognition system, and a job organization system. The document acquisition system receives jobs wherein each job containing at least one electronic document. The document feature recognition system automatically extracts image and text features from each received document. The document classification system automatically classifies recognized electronic documents by finding the best match between the extracted features of each of the document and feature sets associated with each category of document. The document recognition training system automatically trains the feature set for each corresponding category of documents, wherein the training system using extracted features of unrecognized documents automatically modifies the feature set for a document category.

Abstract: A method for monitoring the depth of at least one via (11) in a wafer including the steps of arranging the via (11) as a capacitive plate (21), providing a corresponding capacitive plate (23), applying an electrical potential difference to the via (11) and the corresponding capacitive plate (23), measuring the resultant capacitance between the via (11) and a corresponding capacitive plate (23) and determining the depth of the at least one via (11) by the capacitance.

Abstract: A method for monitoring the depth of at least one via (11) in a wafer comprising the steps of arranging the via (11) as a capacitive plate (21), providing a corresponding capacitive plate (23), applying an electrical potential difference to the via (11) and the corresponding capacitive plate (23), measuring the resultant capacitance between the via (11) and a corresponding capacitive plate (23) and determining the depth of the at least one via (11) by the capacitance.