Abstract: A method for providing automated predictive analysis for a case management system is disclosed and includes providing, by a server, a case management system comprising configuration information defining a plurality of case attributes and performance criteria comprising at least one performance criterion, and comprising case management data associated with the plurality of case attributes and a plurality of cases, and automatically determining a projected outcome associated with a performance criterion included in the configuration information. The method also includes identifying a correlation between a case attribute and the projected outcome based on case management data associated with the case attribute and/or case management data associated with the performance criterion, generating a prediction model based on the correlation and providing a prediction relating to the projected outcome based on the correlation.

Abstract: A method for providing automated predictive analysis for a case management system is disclosed and includes providing, by a server, a case management system comprising configuration information defining a plurality of case attributes and performance criteria comprising at least one performance criterion, and comprising case management data associated with the plurality of case attributes and a plurality of cases, and automatically determining a projected outcome associated with a performance criterion included in the configuration information. The method also includes identifying a correlation between a case attribute and the projected outcome based on case management data associated with the case attribute and/or case management data associated with the performance criterion, generating a prediction model based on the correlation and providing a prediction relating to the projected outcome based on the correlation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. Data for a computer implemented process is in a set of related data objects in a data store with each object in the set of related data objects representing an entity modelled in the process. A number of levels for a multi-dimensional aggregation associated with a request is determined where each level of the multi-dimensional aggregation represents a different dimension of data values to be aggregated. Data is aggregated at the levels of aggregation based on the relationships between parent objects and children objects. The data for a final level of aggregation is output to a user interface. The final result includes multiple dimensions of data.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: A method for providing automated predictive analysis for a case management system is disclosed and includes providing, by a server, a case management system comprising configuration information defining a plurality of case attributes and performance criteria comprising at least one performance criterion, and comprising case management data associated with the plurality of case attributes and a plurality of cases, and automatically determining a projected outcome associated with a performance criterion included in the configuration information. The method also includes identifying a correlation between a case attribute and the projected outcome based on case management data associated with the case attribute and/or case management data associated with the performance criterion, generating a prediction model based on the correlation and providing a prediction relating to the projected outcome based on the correlation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Abstract: A system for detecting and evading vehicle identification means (VIM), comprising: locating device, control device having a plurality of I/O channels, each adapted to receive or transmit serial or parallel data, processing device, electronic storage device comprising at least one database of known VIM coordinates and identification prevention device (IPD) adapted to automatically prevent identification of the vehicle's license plate number, owner, driver or any part or passenger of the vehicle.

Abstract: A system for detecting and evading vehicle identification means (VIM), comprising: locating means, control means having a plurality of I/O channels, each adapted to receive or transmit serial or parallel data, processing means, electronic storage means comprising at least one database of known VIM coordinates and identification prevention device (IPD) adapted to automatically prevent identification of the vehicle's license plate number, owner, driver or any part or passenger of the vehicle.

Abstract: A system for detecting and evading vehicle identification means (VIM), comprising: locating means, control means having a plurality of I/O channels, each adapted to receive or transmit serial or parallel data, processing means, electronic storage means comprising at least one database of known VIM coordinates and identification prevention device (IPD) adapted to automatically prevent identification of the vehicle's license plate number, owner or driver.

Abstract: A system for detecting and evading vehicle identification means (VIM), comprising: locating means, control means having a plurality of I/O channels, each adapted to receive or transmit serial or parallel data, processing means, electronic storage means comprising at least one database of known VIM coordinates and identification prevention device (IPD) adapted to automatically prevent identification of the vehicle's license plate number, owner or driver.