Intracerebral Semantic Space for Rapid Material Evaluation
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Solution Overview
Problem
Conventional methods for evaluating materials are cumbersome and time-consuming, requiring new brain activity measurements for each evaluation, making quick and easy assessments impractical.
Innovation Solution
A material evaluating method that builds an intracerebral semantic space based on brain activity and language descriptions, allowing for the estimation of new material positions within this space without requiring new brain activity measurements, using natural language processing to project content and object words into the semantic space for evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional brain activity measurement methods are used for each new material evaluation, then measurement precision is maintained, but evaluation time and productivity deteriorate
Solution Approach 1:
The patent performs preliminary brain activity measurements using training materials before actual evaluation. An intracerebral semantic space is built in advance by measuring brain activity in response to training materials and associating it with language descriptions. This preliminary space model enables subsequent evaluations to be performed without new brain activity measurements, thus maintaining precision while improving productivity.
Solution Approach 2:
The patent creates a computational copy of the intracerebral semantic space based on preliminary brain activity measurements. This copied semantic space model is then used to evaluate new materials by projecting their language descriptions into the pre-built space, eliminating the need for repeated physical brain activity measurements while preserving evaluation accuracy.
2Reliability
If brain activity measurements are performed for every new material, then evaluation reliability is maintained, but loss of time increases
Solution Approach 1:
The system performs preliminary brain activity measurements and builds the intracerebral semantic space in advance. This preliminary action creates a reliable reference model that can be reused for multiple evaluations, maintaining reliability while avoiding repeated time-consuming measurements for each new material.
Solution Approach 2:
The intracerebral semantic space built from training materials serves multiple evaluation purposes universally. Once the semantic space is constructed, it can evaluate any new material by projecting its language description, making the system multi-functional and eliminating the need for material-specific brain activity measurements.
3Measurement precision
If traditional evaluation methods are used, then measurement accuracy is preserved, but device complexity and operation difficulty increase
Solution Approach 1:
The patent introduces an intermediary computational model (intracerebral semantic space) that mediates between brain activity measurements and material evaluations. This intermediary allows evaluations to be performed by projecting language descriptions into the pre-built space, simplifying operations while preserving the precision established during the preliminary brain activity measurements.
Solution Approach 2:
The patent replaces the mechanical process of performing physical brain activity measurements for each evaluation with a computational substitution. The pre-built intracerebral semantic space model computationally projects new material descriptions to generate evaluations, eliminating the need for repeated mechanical measurement processes while maintaining accuracy.
Data Source
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AI summary
A material evaluating method includes: a brain activity measuring step of presenting a training material to a test subject and measuring a brain activity by using a brain activity measuring unit; a semantic space building step of building an intracerebral semantic space representing an intracerebral semantic relation between the brain activity and a word appearing in a language description on the basis of a measurement result acquired in the brain activity measuring step and the language description acquired by performing natural language processing for a content of the training material by using a semantic space building unit; a first estimation step of estimating a first position corresponding to a content of a new material in the intracerebral semantic space from a language description acquired by performing natural language processing for the content of the new material by using a material estimating unit; a second estimation step of estimating a second position corresponding to an object word in the intracerebral semantic space from the object word representing an object concept of the new material by using an object estimating unit; and an evaluation step of evaluating the new material on the basis of the first position estimated in the first estimation step and the second position estimated in the second estimation step by using an evaluation processing unit.