Abstract:
Technologies for displaying sort results on a computing device includes determining a plurality of sort criteria of the set of data items to be sorted and associating a visual property to each sort criteria. A sort priority of sort criteria may also be determined. The set of data items are sorted based on the sort criteria and sort priority. The sort result is displayed using the visual properties of identify the sorting order of each corresponding sort criteria. The visual properties may include, for example, the display location, size, color, animation, or other visual aspect of the data items.
Abstract:
Technologies for displaying supplemental interface tiles on a user interface of a computing device include determining supplemental information and/or available user interactions associated with a user interface tile displayed on the user interface. A supplemental interface tile is displayed in association with the user interface tile in response to a user selecting the user interface tile. The supplemental information and/or an interaction widget corresponding to the available user interactions may be displayed on the supplemental interface tile based on the selection gesture used by the user to select the user interface tile.
Abstract:
Technologies for displaying notifications on a mobile computing device includes determining a notification category for each notification, determining a priority level for each notification in each notification category, and determining a priority order of the notification categories. The notification categories are displayed as notification containers in which the associated notifications are displayed. Each notification may be displayed as separate tile having a location, size, color, and/or other visual property based on the relative priority level of the individual notification.
Abstract:
Technologies are provided in embodiments to detect malware. The embodiments are configured to receive an entropy rate of a potentially affected system. The embodiments are further configured to compare the entropy rate to an average entropy rate, and to determine a probability that the potentially affected system is infected with malware. The probability is based, at least in part, on a result of the comparison. More specific embodiments can include the received entropy rate being generated, at a least in part, by a genetic program. Additional embodiments can include a configuration to provide the potentially affected system with a specified time-span associated with the genetic program. The specified time-span indicates an amount of time to observe context information on the potentially affected system. In at least some embodiments, the result of the comparison includes an indicator of whether the entropy rate correlates to an infected system or a healthy system.
Abstract:
Technologies for displaying sort results on a computing device includes determining a plurality of sort criteria of the set of data items to be sorted and associating a visual property to each sort criteria. A sort priority of sort criteria may also be determined. The set of data items are sorted based on the sort criteria and sort priority. The sort result is displayed using the visual properties of identify the sorting order of each corresponding sort criteria. The visual properties may include, for example, the display location, size, color, animation, or other visual aspect of the data items.
Abstract:
Technologies for displaying sort results on a computing device includes determining a plurality of sort criteria of the set of data items to be sorted and associating a visual property to each sort criteria. A sort priority of sort criteria may also be determined. The set of data items are sorted based on the sort criteria and sort priority. The sort result is displayed using the visual properties of identify the sorting order of each corresponding sort criteria. The visual properties may include, for example, the display location, size, color, animation, or other visual aspect of the data items.
Abstract:
Embodiments of techniques and systems for performance of predicted actions are described. In embodiments, a predicted action performance engine (“PAE”) may receive one or probabilities of potential actions that may be performed on a computing device. The PAE may also receive a system context for the computing device describing available resources on the computing device, workload, etc. Based on these probabilities and the system context, the PAE may determine one or more predicted actions and/or resource utilizations which are likely to occur and which may be performed ahead of time. The PAE may then facilitate performance of these actions and/or resource utilizations. Other embodiments may be described and claimed.