18297481. TIMED PARTIAL ORDER IDENTIFICATION FOR TASK LEARNING FROM DATA simplified abstract (TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.)
Contents
TIMED PARTIAL ORDER IDENTIFICATION FOR TASK LEARNING FROM DATA
Organization Name
TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
Inventor(s)
Kandai Watanabe of Boulder CO (US)
Georgios Fainekos of Novi MI (US)
Tomoya Yamaguchi of Plano TX (US)
Danil Prokhorov of Canton MI (US)
TIMED PARTIAL ORDER IDENTIFICATION FOR TASK LEARNING FROM DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 18297481 titled 'TIMED PARTIAL ORDER IDENTIFICATION FOR TASK LEARNING FROM DATA
Simplified Explanation:
This patent application describes a system that processes timed traces to perform a task efficiently.
- The system receives timed traces and stores them in memory.
- It generates a partial order graph of time constraints between the timed traces.
- A transitive reduced partial order graph is then created to eliminate redundant time constraints.
- Finally, a timed partial order graph is generated with the minimum number of clocks needed to explain the time constraints.
Key Features and Innovation:
- Efficient processing of timed traces for task execution.
- Generation of partial order graphs to analyze time constraints.
- Reduction of redundant time constraints for improved accuracy.
- Minimization of clocks required for explaining time constraints.
Potential Applications:
This technology can be applied in various fields such as:
- Task scheduling and optimization.
- Real-time systems design.
- Process automation and control.
Problems Solved:
The system addresses the following issues:
- Efficient handling of timed traces for complex tasks.
- Reduction of redundant time constraints for better analysis.
- Minimization of clocks required for accurate time constraint representation.
Benefits:
The technology offers the following benefits:
- Improved task execution efficiency.
- Enhanced accuracy in analyzing time constraints.
- Optimal resource utilization for task scheduling.
Commercial Applications:
Title: Timed Traces Processing System for Task Efficiency
This technology can be utilized in industries such as:
- Manufacturing for process automation.
- Transportation for route optimization.
- Healthcare for patient scheduling.
Prior Art:
Readers can explore prior research on timed traces processing systems and task scheduling algorithms to understand the evolution of this technology.
Frequently Updated Research:
Stay updated on the latest advancements in task scheduling algorithms and real-time systems design to enhance the efficiency of timed traces processing systems.
Questions about Timed Traces Processing Systems:
1. How does the system handle complex time constraints between timed traces?
- The system generates partial order graphs to analyze and represent time constraints accurately.
2. What are the potential real-world applications of this technology?
- This technology can be applied in various industries for task scheduling, process automation, and route optimization.
Original Abstract Submitted
A system is provided for use with a plurality of timed traces for performing a task. The system includes: a data receiver configured to receive the plurality of timed traces; a memory having instructions stored therein; and a processor configured to execute the instructions stored in the memory to cause the system to: store the received plurality of timed traces into the memory; generate a partial order graph of time constraints between all of the plurality of timed traces; generate a transitive reduced partial order graph from the partial order graph, the transitive reduced partial order graph not including redundant time constraints within the partial order graph; and generate a timed partial order graph from the transitive reduced partial order graph, the timed partial order graph having a minimum number of clocks required to explain the time constraints between all of the plurality of timed traces.
