Structured Experimental Data Completion for Automatic Apparatus Control
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Solution Overview
Problem
Existing methods fail to provide complete experimental conditions for conducting experiments using automatic experimental apparatuses, as parameters are often not disclosed in papers and videos, necessitating the input of all conditions, which conventional extraction techniques cannot fully satisfy.
Innovation Solution
A method involving a controller that creates structured data by extracting first values from information sources and adding second values to blank fields, using both first and second information sources to ensure all experimental conditions are input into an automatic experimental apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If experimental condition data is extracted only from papers and experimental videos, then the extraction process is simple, but the completeness of experimental conditions is insufficient for automatic experimental apparatus operation
Solution Approach 1:
The patent divides the data processing into two distinct segments: extraction of explicit experimental conditions from papers/videos, and supplementation of implicit conditions from field knowledge bases. This segmentation allows each module to focus on specific tasks, improving overall completeness while managing complexity through modular architecture.
Solution Approach 2:
The system performs preliminary action by pre-collecting and structuring field common values and implicit experimental conditions into a knowledge base before the actual experiment execution. This preliminary preparation ensures that when experimental data is extracted, the supplementary information is already available, eliminating the need for complex real-time inference during experiment execution.
2Extent of automation
If all experimental condition parameters are required for automatic experimental apparatus operation, then the experiment can be conducted automatically, but the data extraction process becomes more difficult when parameters are not disclosed
Solution Approach 1:
The patent introduces an intermediary component - the field knowledge base - that mediates between the extracted experimental conditions and the automatic experimental apparatus. When parameters are not disclosed in papers/videos, the intermediary supplies default values from field common knowledge, enabling automatic execution without requiring difficult extraction of every single parameter from source materials.
Solution Approach 2:
The system creates a copy of typical experimental conditions and parameter values from field knowledge bases, which can be used as templates or defaults. Instead of extracting every parameter from scratch, the system copies proven values from the knowledge base and applies them where source data is missing, simplifying the extraction process while maintaining automation capability.
3Reliability
If field common values are supplemented to extracted experimental conditions, then the completeness for automatic operation is improved, but the data processing time increases
Solution Approach 1:
The system performs preliminary action by pre-structuring field common values and implicit conditions into an organized knowledge base during off-line periods. This preliminary organization allows the online processing to simply query and match against pre-prepared data structures, significantly reducing the time penalty for supplementation compared to real-time inference or search.
Solution Approach 2:
The patent changes the state of field knowledge from unstructured or semi-structured information into standardized, queryable parameters that match the experimental apparatus requirements. By transforming the knowledge base into compatible parameter formats in advance, the system enables rapid matching and supplementation during experiment execution, minimizing processing time overhead.
Data Source
AI summary
A method of processing structured data related to an experiment includes creating structured data by using a computer, and generating a control signal for operating an automatic experimental apparatus based on the structured data. The structured data includes a plurality of sets of items and values for conducting a predetermined experiment with the automatic experimental apparatus. The creating the structured data includes extracting, from a first information source, a first value to be input to the set, and adding a second value to a blank field of the set.