Rakesh Pandit - Irvine CA, US Toshiro Fujimori - Laguna Beach CA, US Sam Chan - West Covina CA, US
International Classification:
G06F 3/12
US Classification:
358 115
Abstract:
A method used in a print shop for managing a print job submitted by a customer is described. The print shop includes a plurality of printers connected to a server and a client computer. The server generates a main job ticket based on the customer-submitted print job, and generates a plurality of sub-job tickets based on the main job ticket. The sub-jobs defined by the sub-job tickets collectively accomplish the print job submitted by the customer. The server maintains a database that stores the main job ticket and the sub-job tickets in association with the corresponding main job ticket. The server also monitors the status of the sub-jobs and updates the status of the main job ticket on a user interface of a client computer. When all the sub-jobs are complete, the main job ticket is displayed in the user interface as being complete.
Printing Of Proof Copy With Reduced Resource Usage In A Print Shop Management System
KONICA MINOLTA SYSTEMS LABORATORY, INC. - Huntington Beach CA
International Classification:
G06F 3/12
US Classification:
358 115
Abstract:
A proof copy printing method implemented in a print shop. When a user desires to print a proof copy of a print job while reducing resource usage, the user activates a GUI screen, which allows the user to conveniently set multiple parameters that will achieve reduced resource usage. When printing the proof copy, the values set on the GUI screen are used to temporarily override the corresponding parameter values specified in the job ticket without modifying the job ticket itself. When the user desires to print the job normally, the user activates the GUI screen to cancel the proof mode. The system then prints the job using the job parameter values specified in the job ticket.
Classification Of Synthetic Data Tasks And Orchestration Of Resource Allocation
Various techniques are described for classifying synthetic data tasks and orchestrating a resource allocation between groups of eligible resources for processing the synthetic data tasks. Received synthetic data tasks can be classified by identifying a task category and a corresponding group of eligible resources (e.g., processors) for processing synthetic data tasks in the task category. For example, synthetic data tasks can include generation of source assets, ingestion of source assets, identification of variation parameters, variation of variation parameters, and creation of synthetic data. Certain categories of synthetic data tasks can be classified for processing with a particular group of eligible resources. For example, tasks to ingest synthetic data assets can be classified for processing on a CPU only, while a task to create synthetic data assets can be classified for processing on a GPU only. The synthetic data tasks can be queued and routed for processing by an eligible resource.
Donna Hooker, Katherine Clinton, Ali Dilley, Shanona Groves, Betty Tooley, Angela Fullington, Jenifer Smith, Casey Bruce, Chris Harris, Tony Moore, H Malonson
State University of New York College At Brockport Brockport NY 2001-2005
Community:
Folarin Akingbade, Chad Burdick, Jenessa Wheeler, Paras Patel, Freeman Freeman, Dana Watson, Dave Freedman, Steven Klafehn, Marina Hughes, Samip Kewalramani
"Many of the teachers were mortified when we pointed out they may be exacerbating the invasive species problem," said lead researcher Sam Chan, an Oregon State University invasive species expert, in a statement. "We don't want to discourage the use of live organisms in teaching because they can prov