Abstract: A method to determine transaction distribution among a plurality of transaction processing systems may include calculating estimated handling resources for each of the plurality of transaction processing systems based upon measured actual handling resources and identified scheduled handling resources. Transaction allocations may be determined for each of the transaction processing systems based upon the estimated handling resources.

Abstract: A method to determine transaction distribution among a plurality of transaction processing systems may include calculating estimated handling resources for each of the plurality of transaction processing systems based upon measured actual handling resources and identified scheduled handling resources. Transaction allocations may be determined for each of the transaction processing systems based upon the estimated handling resources.

Abstract: A method and apparatus for performing customer service request allocations based upon real-time data and forecast data, calculates estimated handling resources for each of the transaction processing systems based upon actual handling resources and scheduled handling resources. Customer service transaction workloads are forecasted for the handling resources for each of the transaction processing systems. Then, customer service request allocations are determined using estimated handling resources and the forecasted customer service transaction workload.

Abstract: A method and apparatus for performing customer service request allocations based upon real-time data and forecast data, calculates estimated handling resources for each of the transaction processing systems based upon actual handling resources and scheduled handling resources. Customer service transaction workloads are forecasted for the handling resources for each of the transaction processing systems. Then, customer service request allocations are determined using estimated handling resources and the forecasted customer service transaction workload.

Abstract: A method and apparatus are provided for performing staffing-based percentage-allocation routing using real-time data. According to one aspect of the present invention, transaction allocation is determined using both scheduled and actual handling resources. Actual handling resources associated with each of several transaction processing systems, such as automatic call distributors (ACDs), are measured at times t and t+n. Scheduled handling resources associated with each of the transaction processing systems for times t and t+n are also identified. Then, estimated handling resources are calculated for each of the transaction processing systems for time t+n based upon the actual handling resources and the scheduled handling resources. Finally, based upon the estimated handling resources, transaction allocations for each of the transaction processing systems are determined. According to another aspect of the present invention, a virtual call center is provided.

Abstract: Image rotation systems and methods optimally rotate high addressability binary images by transforming the high addressability image to a quasi-grayscale image having normal addressability. A degree of low-pass filtering may be used in conjunction with resampling the image in the process of generating the normal addressability image for rotation. The quasi-grayscale image is then rotated. The rotated quasi-grayscale image is then converted back to a high addressability binary image using a high addressability halftoning process. The systems and methods provide a process wherein high addressability binary images are rotated without introducing gray-level contours or pattern artifacts such as moiré. Further, the apparatus and method provide compact rotation of high addressability images. The density and edge integrity of the processed image are maintained without introducing false contours.

Abstract: Image rotation systems and methods optimally rotate high addressability binary images in a compact manner. High addressability bit pixels are clustered to form multi-bit pixels. The multi-bit pixel image is rotated +/−90°. A pixel mapping method is employed that realigns high addressability pixels within each target group of pixels in a manner that maintains edge integrity, maintains density, and does not introduce additional false contours. Information regarding neighboring pixel values is used to determine edge information about a given high addressability target pixel group. The edge information includes an edge slope and edge location of the high addressability target pixel group. Based on the rotation angle and the edge information of the pixel group, the target high addressability pixel group is mapped to a preferred pattern. After mapping to a preferred pattern, the high addressability pixel group is rotated.