An information handling system includes a host processing complex with a memory, and a baseboard management controller (BMC) with a processor and a video capture and difference engine (VCDE). The processor receives a memory compare command. The memory compare command includes a first pointer to a first block of the memory, a second pointer to a second block of the memory, and a memory block size. The processor further determines whether the memory block size is greater than a threshold, and forwards the memory compare command to the VCDE when the memory block size is greater than the threshold. The VCDE compares contents of the first block to contents of the second block in response to receiving the memory compare command.

An information handling system includes a host processing complex with a memory, and a baseboard management controller (BMC) with a processor and a video capture and difference engine (VCDE). The processor receives a memory compare command. The memory compare command includes a first pointer to a first block of the memory, a second pointer to a second block of the memory, and a memory block size. The processor further determines whether the memory block size is greater than a threshold, and forwards the memory compare command to the VCDE when the memory block size is greater than the threshold. The VCDE compares contents of the first block to contents of the second block in response to receiving the memory compare command.

A method for displaying a secure or forgery-proof identity indicator on a screen using a display controller displaying the content of a memory unit of the graphic circuit on the screen, includes: drawing, by a client application, a graphic to be displayed on the screen into a client-specific region of the memory unit of the graphic circuit; drawing an identity indicator belonging to the client application into a memory region outside of the client-specific region; displaying the client-specific region of the memory unit of the graphic circuit on the screen; and simultaneously displaying the identity indicator from the memory region outside of the client-specific region on the screen. For displaying the identity indicator from the memory region outside of the client-specific region, access is only possible from the display controller such that the display of the identity indicator is secure or forgery-proof.

A method for displaying a secure or forgery-proof identity indicator on a screen using a display controller displaying the content of a memory unit of the graphic circuit on the screen, includes: drawing, by a client application, a graphic to be displayed on the screen into a client-specific region of the memory unit of the graphic circuit; drawing an identity indicator belonging to the client application into a memory region outside of the client-specific region; displaying the client-specific region of the memory unit of the graphic circuit on the screen; and simultaneously displaying the identity indicator from the memory region outside of the client-specific region on the screen. For displaying the identity indicator from the memory region outside of the client-specific region, access is only possible from the display controller such that the display of the identity indicator is secure or forgery-proof.

A method, system and computer-usable medium are disclosed for capturing an image rendered by a target application. One general aspect includes a computer-implemented method for capturing an image, the method including: intercepting API calls made by a target application to a graphics display driver, where the API calls made to the graphics display driver by the target application are made using a graphics rendering API library; and using the intercepted API calls to construct a copy of a frame buffer of the image, where the copy of the frame buffer is constructed independent of the graphics display driver. Certain embodiments may include corresponding stand-alone and/or network computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform one or more of these actions.

A method, system and computer-usable medium are disclosed for capturing an image rendered by a target application. One general aspect includes a computer-implemented method for capturing an image, the method including: intercepting API calls made by a target application to a graphics display driver, where the API calls made to the graphics display driver by the target application are made using a graphics rendering API library; and using the intercepted API calls to construct a copy of a frame buffer of the image, where the copy of the frame buffer is constructed independent of the graphics display driver. Certain embodiments may include corresponding stand-alone and/or network computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform one or more of these actions.

An interactive display case having a first frame, a plurality of storage areas within the first frame, a second frame, and processing circuitry. The processing circuitry is configured to detect an object passing through the interior of the second frame, identify an area within the interior of the second frame in which the object passes, where the area corresponding to one of the storage areas, and generate interaction data corresponding to the identified area.

An interactive display case having a first frame, a plurality of storage areas within the first frame, a second frame, and processing circuitry. The processing circuitry is configured to detect an object passing through the interior of the second frame, identify an area within the interior of the second frame in which the object passes, where the area corresponding to one of the storage areas, and generate interaction data corresponding to the identified area.

Data may be handled based on compressibility (i.e., whether the data may be further compressed or is not further compressible). A supervised learning model may be trained using a set of known further compressible data and a set of known non-compressible data. Using these data sets, the model may generate weighting factors and bias for the particular data sets. The trained model may then be used to evaluate a set of unclassified data.

Data may be handled based on compressibility (i.e., whether the data may be further compressed or is not further compressible). A supervised learning model may be trained using a set of known further compressible data and a set of known non-compressible data. Using these data sets, the model may generate weighting factors and bias for the particular data sets. The trained model may then be used to evaluate a set of unclassified data.