Abstract: An object ID-centered workflow method utilizes an object identifier (ID) associated with an object. Forensic identification of serialization elements of the object ID enables access to a registry of workflows.

Abstract: Techniques for classifying records in a dataset are described. The method includes identifying a set of features of a target record and assigning a scoring metric to each feature in the set of features. The method also includes processing the set of features based on the scoring metric to obtain a reduced subset of features and an expanded subset of features. The method also includes searching a store of electronic records using the reduced subset of features to obtain a reduced subset of electronic records. The method also includes searching the reduced subset of electronic records using the expanded subset of features to obtain a set of matching electronic records.

Abstract: An object ID-centered workflow method utilizes an object identifier (ID) associated with an object. Forensic identification of serialization elements of the object ID enables access to a registry of workflows.

Abstract: An object ID-centered workflow method utilizes an object identifier (ID) associated with an object. Forensic identification of serialization elements of the object ID enables access to a registry of workflows.

Abstract: In one example in accordance with the present disclosure, a method is described. According to the method, a computing device acquires data related to a variable data component. The computing device then authenticates at least one of the computing device and the proper user of the computing device. Upon authentication of the computing device and/or proper user of the computing device, a downstream workflow is authorized. The downstream workflow is defined by the data associated with the variable data component and enabled via the authentication of the computing device and/or proper user of the computing device.

Abstract: Techniques for classifying records in a dataset are described. The method includes identifying a set of features of a target record and assigning a scoring metric to each feature in the set of features. The method also includes processing the set of features based on the scoring metric to obtain a reduced subset of features and an expanded subset of features. The method also includes searching a store of electronic records using the reduced subset of features to obtain a reduced subset of electronic records. The method also includes searching the reduced subset of electronic records using the expanded subset of features to obtain a set of matching electronic records.

Abstract: An object ID-centered workflow method utilizes an object identifier (ID) associated with an object. Forensic identification of serialization elements of the object ID enables access to a registry of workflows.

Abstract: In one example in accordance with the present disclosure a method is described. According to the method, data associated with a variable data component is captured by a user computing device is received via a network. A user is authenticated by comparing biometric information for the user against a database of valid users. Responsive to an authentication of the user, role-based workflows are triggered. The role-based workflows are based on the biometric information for the user received from the user computing device and the data associated with the variable data component.

Abstract: In one example in accordance with the present disclosure, a method is described. According to the method, a computing device acquires data related to a variable data component. The computing device then authenticates at least one of the computing device and the proper user of the computing device. Upon authentication of the computing device and/or proper user of the computing device, a downstream workflow is authorized. The downstream workflow is defined by the data associated with the variable data component and enabled via the authentication of the computing device and/or proper user of the computing device.

Abstract: Examples herein disclose receiving and identifier associated with a first void pantograph and identifying a second void pantograph based on the received identifier. The examples facilitate authentication of the first void pantograph by making available the second void pantograph.

Abstract: Example implementations relate to multiple payload pantograph. Some examples may include a first pattern generation engine to generate a first pattern. The first pattern may be a data-bearing pattern encoding a first payload. Additionally, some examples may include a second pattern generation engine to generate a second pattern, the second pattern (by itself or in combination with the first pattern) may represent a second payload. The second payload may be camouflaged by a combination of the first pattern and the second pattern. Some examples may also include a pantograph generation engine to generate a multiple payload pantograph including the first pattern and the second pattern. The multiple payload pantograph may include the first pattern in one of the pantograph background or the pantograph foreground.

Abstract: A counterfeit identification performance attribute (SIPA) sensitivity to changes in resolution of the image for features of an image is determined. The CIPA sensitivity for the features is used to choose at least one feature to determine whether the image on a sample is a counterfeit.

Abstract: Personalized learning based on functional summarization is disclosed. One example is a system including a content processor, a plurality of summarization engines, at least one meta-algorithmic pattern, an evaluator, and a selector. The content processor provides course material to be learned, the course material selected from a corpus of educational content, and identifies retained material indicative of a portion of the course material retained by user. Each of the plurality of summarization engines provides a differential summary indicative of differences between the course material and the retained material. The at least one meta-algorithmic pattern is applied to at least two differential summaries to provide a meta-summary using the at least two differential summaries. The evaluator determines a value of each differential summary and meta-summary.

Abstract: Examples herein disclose receiving and identifier associated with a first void pantograph and identifying a second void pantograph based on the received identifier. The examples facilitate authentication of the first void pantograph by making available the second void pantograph.

Abstract: Example implementations relate to multiple payload pantograph. Some examples may include a first pattern generation engine to generate a first pattern. The first pattern may be a data-bearing pattern encoding a first payload. Additionally, some examples may include a second pattern generation engine to generate a second pattern, the second pattern (by itself or in combination with the first pattern) may represent a second payload. The second payload may be camouflaged by a combination of the first pattern and the second pattern. Some examples may also include a pantograph generation engine to generate a multiple payload pantograph including the first pattern and the second pattern. The multiple payload pantograph may include the first pattern in one of the pantograph background or the pantograph foreground.

Abstract: A counterfeit identification performance attribute (SIPA) sensitivity to changes in resolution of the image for features of an image is determined. The CIPA sensitivity for the features is used to choose at least one feature to determine whether the image on a sample is a counterfeit.

Abstract: A counterfeit identification performance attribute (CIPA) sensitivity to changes in resolution of the image for features of an image is determined (102). The CIPA sensitivity for the features is used to choose at least one feature to determine whether the image on a sample is a counterfeit (106).

Abstract: A reading device reads ambiguous target elements of an authentication target printed on a medium. Each ambiguous target element has a number of different manners by which the ambiguous target element can be interpreted by the reading device. The authentication target as read by the reading device is compared against an authentication signature of the reading device. The authentication signature specifies for each ambiguous target element an expected manner by which the reading device interprets the ambiguous target element as one of the different manners by which the ambiguous target element can be interpreted. Where the authentication target as read by the reading device matches the authentication signature of the reading device, the reading device is signaled as having passed authentication.

Abstract: An apparatus has a surface that includes a two dimensional barcode and a Radio Frequency Identification (RFID) antenna printed on the two dimensional barcode. The RFID antenna and the two dimensional barcode are formed from a conductive ink.

Abstract: Methods, and apparatus for performing methods, for selecting a classifier engine. Methods include, for two or more portions of a set of items of known classification, classifying members of each portion using a particular classifier engine; selecting a portion of the set of items whose classifications satisfy a first criteria; classifying members of the selected portion of the set of items using two or more classifier engines; and selecting a classifier engine whose classification of the selected portion of the set of items satisfies a second criteria.