Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for identifying a target value in a data set are presented. A request for a first target value in a data array may be received, wherein the request comprises first reference value. The data array may comprise a plurality of values and a plurality of value types included in one or more tables in a computer-implemented spreadsheet application. An index comprising a plurality of sorted reference numbers corresponding to a plurality of values in the data array may be generated based on the request. The index may be searched, and based at least on the search, the first reference value may be identified. In additional examples, the index may be cached and utilized to process additional target value requests that reference an overlapping range value with the first request.

Abstract: In various implementations, a calculation manger identifies one or more external references within a workbook, wherein the workbook resides in a spreadsheet environment comprising multiple workbooks. The recalculation manager then identifies a scope of a recalculation, triggered by an event in the workbook, based on one or more factors comprising the one or more external references. A recalculation engine then performs the recalculation within the identified scope.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for identifying a target value in a data set are presented. A request for a first target value in a data array may be received, wherein the request comprises first reference value. The data array may comprise a plurality of values and a plurality of value types included in one or more tables in a computer-implemented spreadsheet application. An index comprising a plurality of sorted reference numbers corresponding to a plurality of values in the data array may be generated based on the request. The index may be searched, and based at least on the search, the first reference value may be identified. In additional examples, the index may be cached and utilized to process additional target value requests that reference an overlapping range value with the first request.

Abstract: Efficient data structures are generated to enforce permissions on a multi-dimensional representation in a performance management application. A model site is generated having at least one model with at least one dimension. User permissions and group permissions are set for the model. The user permission and the group permissions are deployed to a relational database. A collective user permission table is generated based on the user permissions and the group permissions. Thus, an end user may receive permissions associated with a model and permissions associated with particular dimensions of a model without an inefficient consumption of resources.

Abstract: Video signatures are generated when a small change in video information between consecutive frames N?1 and N is followed by a large change in video information between consecutive frames N and N+1. Information from frames N and/or N+1 is used to form a video signature.

Abstract: Video signatures are generated when a small change in video information between consecutive frames N?1 and N is followed by a large change in video information between consecutive frames N and N+1. Information from frames N and/or N+1 is used to form a video signature.

Abstract: Efficient data structures are generated to enforce permissions on a multi-dimensional representation in a performance management application. A model site is generated having at least one model with at least one dimension. User permissions and group permissions are set for the model. The user permission and the group permissions are deployed to a relational database. A collective user permission table is generated based on the user permissions and the group permissions. Thus, an end user may receive permissions associated with a model and permissions associated with particular dimensions of a model without an inefficient consumption of resources.

Abstract: Efficient data structures are generated to enforce permissions on a multi-dimensional representation in a performance management application. A model site is generated having at least one model with at least one dimension. User permissions and group permissions are set for the model. The user permission and the group permissions are deployed to a relational database. A collective user permission table is generated based on the user permissions and the group permissions. Thus, an end user may receive permissions associated with a model and permissions associated with particular dimensions of a model without an inefficient consumption of resources.

Abstract: Efficient data structures are generated to enforce permissions on a multi-dimensional representation in a performance management application. A model site is generated having at least one model with at least one dimension. User permissions and group permissions are set for the model. The user permission and the group permissions are deployed to a relational database. A collective user permission table is generated based on the user permissions and the group permissions. Thus, an end user may receive permissions associated with a model and permissions associated with particular dimensions of a model without an inefficient consumption of resources.