The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating an identity resolution model from a ground truth data set to accurately match users across one or more digital content providers to perform analyses of user activities across the one or more digital content providers. For example, the systems described herein can generate a ground truth data set of known users and utilize the ground truth data set to generate an identity resolution model for one or more digital content providers based on predicted user identities. Furthermore, in one or more embodiments, the systems utilize the identity resolution model to accurately resolve and match user identities between one or more digital content providers and assign universal identifiers to the user identities. Moreover, the disclosed systems can utilize the universal identifiers to provide analytical insights of user actions between the one or more digital content providers.

The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating an identity resolution model from a ground truth data set to accurately match users across one or more digital content providers to perform analyses of user activities across the one or more digital content providers. For example, the systems described herein can generate a ground truth data set of known users and utilize the ground truth data set to generate an identity resolution model for one or more digital content providers based on predicted user identities. Furthermore, in one or more embodiments, the systems utilize the identity resolution model to accurately resolve and match user identities between one or more digital content providers and assign universal identifiers to the user identities. Moreover, the disclosed systems can utilize the universal identifiers to provide analytical insights of user actions between the one or more digital content providers.

Techniques that facilitate graph similarity analytics are provided. In one example, a system includes an information component and a similarity component. The information component generates a first information index indicative of a first entropy measure for a first graph-structured dataset associated with a machine learning system. The information component also generates a second information index indicative of a second entropy measure for a second graph-structured dataset associated with the machine learning system. The similarity component determines similarity between the first graph-structured dataset and the second graph-structured dataset based on a graph similarity computation associated with the first information index and the second information index.

Techniques that facilitate graph similarity analytics are provided. In one example, a system includes an information component and a similarity component. The information component generates a first information index indicative of a first entropy measure for a first graph-structured dataset associated with a machine learning system. The information component also generates a second information index indicative of a second entropy measure for a second graph-structured dataset associated with the machine learning system. The similarity component determines similarity between the first graph-structured dataset and the second graph-structured dataset based on a graph similarity computation associated with the first information index and the second information index.

Apparatuses, systems, and methods related to determination of a match between data values stored by several arrays are described. A system using the data values may manage performance of functions, including automated functions critical for prevention of damage to a product, personnel safety, and/or reliable operation, based on whether the data values match. For instance, one apparatus described herein includes a plurality of arrays of memory cells formed on a single memory chip. The apparatus further includes comparator circuitry configured to compare data values stored by two arrays selected from the plurality to determine whether there is a match between the data values stored by the two arrays. The apparatus further includes an output component configured to output data values of one of the two arrays responsive to determination of the match between the data values stored by the two arrays.

Apparatuses, systems, and methods related to determination of a match between data values stored by several arrays are described. A system using the data values may manage performance of functions, including automated functions critical for prevention of damage to a product, personnel safety, and/or reliable operation, based on whether the data values match. For instance, one apparatus described herein includes a plurality of arrays of memory cells formed on a single memory chip. The apparatus further includes comparator circuitry configured to compare data values stored by two arrays selected from the plurality to determine whether there is a match between the data values stored by the two arrays. The apparatus further includes an output component configured to output data values of one of the two arrays responsive to determination of the match between the data values stored by the two arrays.

The present invention provides a target detection method and an unmanned aerial vehicle. The method includes: obtaining an image of a target, and obtaining a feature model of the target according to the image of the target; determining whether the target is lost; and if it is determined that the target is lost: obtaining a currently photographed first frame of image; obtaining an N.sup.th frame of image which is photographed after the first frame of image, N being an integer greater than 0; obtaining, according to the first frame of image and the N.sup.th frame of image, a candidate area which possibly includes the target; and determining, according to the feature model of the target and the candidate area, whether the N.sup.th frame of image includes the target. A detection efficiency is high by using the target detection method provided in the present invention.

An optical element for an optical system that operates with working light in the wavelength spectrum of extreme ultraviolet light or soft X-ray radiation, in particular an optical system for EUV microlithography, that includes an absorber layer (12) for EUV or soft X-ray radiation. The absorber layer extends along an optically effective surface and has a thickness that is defined transversely with respect to the optically effective surface, wherein the thickness of the absorber layer varies over the optically effective surface. Also disclosed is a mirror formed by at least one roughened surface of the mirror, the roughness of which varies over the surface. In addition, an illumination system for an EUV projection exposure apparatus, and a method for producing a corresponding intensity adaptation filter are disclosed.

Implementations of a system, method and apparatus described herein receive, for a configuration item in a configuration management database, status indicating an operational state and an automation state associated with the configuration item, and determine whether a conflict will occur with at least one of the operational state or the automation state of the configuration item as a result of a process affecting the configuration item. When the conflict will not occur, a change is made to at least one of the operational state or the automation state of the configuration item in accordance with the process. Upon a conclusion of the process, the change is removed. If the conflict will occur, the process not allowed to continue.

Implementations of a system, method and apparatus described herein receive, for a configuration item in a configuration management database, status indicating an operational state and an automation state associated with the configuration item, and determine whether a conflict will occur with at least one of the operational state or the automation state of the configuration item as a result of a process affecting the configuration item. When the conflict will not occur, a change is made to at least one of the operational state or the automation state of the configuration item in accordance with the process. Upon a conclusion of the process, the change is removed. If the conflict will occur, the process not allowed to continue.