Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Examples described herein relate to a display engine. In some examples, at least one processor is to generate one or more planes of a frame and store the generated one or more planes of a frame into the at least one memory. In some examples, the at least one processor is to determine whether a plane in the frame is a candidate plane for compression. In some examples, for the candidate plane for compression, based on the candidate plane not being subject to compression, the at least one processor is to adjust a plane level of the candidate plane to subject the candidate plane to compression. In some examples, the plane level of the candidate plane to subject the candidate plane to compression is a bottom most level. In some examples, for the candidate plane for compression, based on the candidate plane not being subject to compression and the candidate plane including content that would be occluded by an upper level plane, the at least one processor is to retain a plane level of the candidate plane.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Embodiments may include systems, techniques, methods, apparatus and/or device to receive an input selecting one or more areas of a display of the computing device, leaving one or more other areas of the display unselected, and to apply a masking layer to mask either pixels of the one or more selected areas or pixels of the one or more unselected areas to cause the masked pixels to be dimmed, to reduce power consumption by the display. Embodiments may further include where the one or more of the selected areas include a focus area of interest, and to apply the masking layer to mask pixels of the one or more unselected areas to cause the masked pixels to be dimmed. Embodiments may be implemented via software without directly interacting with hardware. Other embodiments may be described or claimed.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Examples described herein relate to a display engine. In some examples, at least one processor is to generate one or more planes of a frame and store the generated one or more planes of a frame into the at least one memory. In some examples, the at least one processor is to determine whether a plane in the frame is a candidate plane for compression. In some examples, for the candidate plane for compression, based on the candidate plane not being subject to compression, the at least one processor is to adjust a plane level of the candidate plane to subject the candidate plane to compression. In some examples, the plane level of the candidate plane to subject the candidate plane to compression is a bottom most level. In some examples, for the candidate plane for compression, based on the candidate plane not being subject to compression and the candidate plane including content that would be occluded by an upper level plane, the at least one processor is to retain a plane level of the candidate plane.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for reduced computing device power consumption. Example methods disclosed herein includes detecting frame updates corresponding to input frames to be presented by a display, and causing a programmable timer to generate second interrupts corresponding to first interrupts generated by a display engine, the second interrupts to be generated when there are no frame updates detected for at least a first duration of time defined by a first threshold. Example methods further include causing the display engine to transition to a low power state when (1) the programmable timer is configured to generate the second interrupts and (2) no frame updates have been detected for at least a second duration of time following the first duration of time, the second duration of time defined by a second threshold.

Abstract: Embodiments may include systems, techniques, methods, apparatus and/or device to receive an input selecting one or more areas of a display of the computing device, leaving one or more other areas of the display unselected, and to apply a masking layer to mask either pixels of the one or more selected areas or pixels of the one or more unselected areas to cause the masked pixels to be dimmed, to reduce power consumption by the display. Embodiments may further include where the one or more of the selected areas include a focus area of interest, and to apply the masking layer to mask pixels of the one or more unselected areas to cause the masked pixels to be dimmed. Embodiments may be implemented via software without directly interacting with hardware. Other embodiments may be described or claimed.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for reduced computing device power consumption. Example methods disclosed herein includes detecting frame updates corresponding to input frames to be presented by a display, and causing a programmable timer to generate second interrupts corresponding to first interrupts generated by a display engine, the second interrupts to be generated when there are no frame updates detected for at least a first duration of time defined by a first threshold. Example methods further include causing the display engine to transition to a low power state when (1) the programmable timer is configured to generate the second interrupts and (2) no frame updates have been detected for at least a second duration of time following the first duration of time, the second duration of time defined by a second threshold.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.

Abstract: Some examples relate generally to computer architecture software data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data.