Abstract: A method and system are provided for data driven shrinkage compensation. The method includes calculating, by at least one processor operatively coupled to a memory device, one or more dimensions of an object modeled in a file from one or more directional strands disposed between facets of one or more predetermined facet pairs. The method further includes predicting, by the processor, dimensional changes in the one or more directional strands as a result of the fabrication of the object using an additive manufacturing process based on a shape shrinkage model. The method further includes correcting, by the processor, coordinate data of at least one facet of the one or more predetermined facet pairs to compensate for the one or more predicted dimensional changes in the one or more directional strands.

Abstract: A cascading convolutional neural network (CCNN) comprising a plurality of convolutional neural networks (CNNs) that are trained by weighting training data based on loss values of each training datum between CNNs of the CCN. The CCNN can receiving an input image from plurality of images, classify the input image using the CCNN, and present a classification of the input image.

Abstract: A method, a computing system and a computer program product are provided. A link for use by a user to access a file is created. Content of the file is encrypted using a common key. The common key is encrypted using a public key of the user and is registered in the link. Access rights regarding the file are set for the user and registered in the link. The link includes information for use by the user to access the file when the access rights indicate that the user is authorized to access the file.

Abstract: A method, a computing system and a computer program product are provided. A link for use by a user to access a file is created. Content of the file is encrypted using a common key. The common key is encrypted using a public key of the user and is registered in the link. Access rights regarding the file are set for the user and registered in the link. The link includes information for use by the user to access the file when the access rights indicate that the user is authorized to access the file.

Abstract: Neural network classification may be performed by inputting a training data set into each of a plurality of first neural networks, the training data set including a plurality of samples, obtaining a plurality of output value sets from the plurality of first networks, each output value set including a plurality of output values corresponding to one of the plurality of samples, each output value being output from a corresponding first neural network in response to the inputting of one of the samples of the training data set, inputting the plurality of output value sets into a second neural network, and training the second neural network to output an expected result corresponding to each sample in response to the inputting of a corresponding output value set.

Abstract: Neural network classification may be performed by inputting a training data set into each of a plurality of first neural networks, the training data set including a plurality of samples, obtaining a plurality of output value sets from the plurality of first neural networks, each output value set including a plurality of output values corresponding to one of the plurality of samples, each output value being output from a corresponding first neural network in response to the inputting of one of the samples of the training data set, inputting the plurality of output value sets into a second neural network, and training the second neural network to output an expected result corresponding to each sample in response to the inputting of a corresponding output value set.

Abstract: A method and system are provided for data driven shrinkage compensation. The method includes calculating, by at least one processor operatively coupled to a memory device, one or more dimensions of an object modeled in a file from one or more directional strands disposed between facets of one or more predetermined facet pairs. The method further includes predicting, by the processor, dimensional changes in the one or more directional strands as a result of the fabrication of the object using an additive manufacturing process based on a shape shrinkage model. The method further includes correcting, by the processor, coordinate data of at least one facet of the one or more predetermined facet pairs to compensate for the one or more predicted dimensional changes in the one or more directional strands.

Abstract: The present invention may be a method, a computer system, and a computer program product. An embodiment of the present invention provides a method for finding a problem in procedures described in a guide document for install and configuration of software. The method comprises calculating, using a dynamic programming matching, a distance between an install-and-configuration log generated by executing the install and configuration of the software according to the guide document at a user-side computer and a log template generated by executing the install and configuration of the software according to the guide document at an administrator-side computer, and finding a problem in the procedures, using the distance.

Abstract: A method, a computing system and a computer program product are provided. A link for use by a user to access a file is created. Content of the file is encrypted using a common key. The common key is encrypted using a public key of the user and is registered in the link. Access rights regarding the file are set for the user and registered in the link. The link includes information for use by the user to access the file when the access rights indicate that the user is authorized to access the file.

Abstract: A method and system are provided for data driven shrinkage compensation. The method includes subdividing, by a polygon subdivider, polygons in a three-dimensional file into facets. The method further includes calculating, by an axis dimension calculator, dimensions of an object from an x-directional strand disposed between two facets of a first predetermined facet pair, a y-directional strand disposed between two facets of second predetermined facet pair, and a z-directional strand disposed between two facets of a third predetermined facet pair. The object is formed from at least some of the polygons. The method also includes predicting, by a dimension change predictor, dimensional changes in the strands based on a shape shrinkage model. The method additionally includes correcting, by a dimension change compensator, x-coordinate data, y-coordinate data, and z-coordinate data of at least one facet of the predetermined facet pairs to compensate for the dimensional changes in the strands.

Abstract: A method for printing and extracting of a barcode for an object includes dividing a barcode into disjointed regions and assigning the disjointed regions to different locations on an object. The disjointed regions are printed on the object at the different locations wherein the disjointed regions are printed visibly or invisibly.

Abstract: The present invention may be a method, a computer system, and a computer program product. An embodiment of the present invention provides a method for judging data consistency in a database. In one embodiment, the method comprises the following: generating a property of data obtained from a first database; associating the property with an attribute of a data model to generate a data property definition; judging whether data obtained from a second database satisfies the data property definition or not; and outputting a result of the judgment. In another embodiment, the method comprises the following: generating a property of data obtained from a database; associating the property with an attribute of a data model to generate a data property definition; judging whether data which is stored in the database satisfies the data property definition or not; and outputting a result of the judgment.

Abstract: A method includes: training a first neural network using a first training dataset; inputting each test data of a first test dataset to the first neural network; calculating output data of the first neural network for each test data of the first test dataset; composing a second training dataset of training data from the first test dataset that causes the first neural network to output data within a first range; and training a second neural network using the second training dataset.

Abstract: A system and method for optimizing (designing) a mask pattern, in which SMO and OPC are collaboratively used to exert a sufficient collaborative effect or are appropriately used in different manners. The method for designing a source and a mask for lithography includes a step (S1) of selecting a set of patterns; a step of performing source mask optimization (SMO) using the set of patterns, under an optical proximity correction (OPC) restriction rule which is used for selectively restricting shifting of an edge position of a polygon when OPC is applied to the set of patterns; and a step (S3, S4) of determining a layout of the mask for lithography, by applying OPC to all patterns constituting the mask for lithography using the source optimized through the SMO.

Abstract: A method for printing and extracting of a barcode for an object includes dividing a barcode into disjointed regions and assigning the disjointed regions to different locations on an object. The disjointed regions are printed on the object at the different locations wherein the disjointed regions are printed visibly or invisibly.

Abstract: A method for printing and extracting of a barcode for an object includes dividing a barcode into disjointed regions and assigning the disjointed regions to different locations on an object. The disjointed regions are printed on the object at the different locations wherein the disjointed regions are printed visibly or invisibly.