Graphical Interface for Cognitive Model Resource Mapping
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Solution Overview
Problem
Existing systems for requirements analysis lack a graphically intuitive human-machine interface, failing to leverage visual knowledge and interactive graphical interfaces, which hinders effective decision-making in complex multi-variable systems-of-systems design and resource allocation.
Innovation Solution
A graphical user interface (GUI) and process that enables users to select and define problems, map tasks and resources, and correlate cognitive models, allowing for visual representation and validation of relationships between tasks, resources, and decision models, facilitating rapid assessments and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing systems for requirements analysis are used, then analysis can be performed, but the interface is not graphically intuitive and visual knowledge is not leveraged
Solution Approach 1:
The patent replaces traditional text-based or form-based requirements analysis interfaces with a graphical user interface that leverages visual knowledge representation. The system uses graphical displays showing visual relationships between requirements, tasks, and resources, allowing users to interact with and analyze complex systems through intuitive visual metaphors rather than complex mechanical interaction with detailed specifications.
Solution Approach 2:
The patent introduces a visual knowledge representation layer as an intermediary between the user and the complex requirements analysis system. This graphical interface acts as a mediator that translates complex system relationships into intuitive visual displays, allowing users to interact with the system through natural visual perception rather than directly manipulating complex data structures.
2Measurement precision
If complex multi-variable systems-of-systems design is analyzed, then comprehensive analysis is achieved, but decision-making efficiency is hindered
Solution Approach 1:
The patent extracts and separates key system relationships and variables into distinct visual elements within the graphical interface. By taking out critical relationships from the complex system and representing them as discrete visual objects with clear spatial relationships, the system allows users to focus on specific aspects of the analysis without being overwhelmed by the full complexity, thereby maintaining comprehensiveness while reducing decision-making time.
Solution Approach 2:
The patent adds a visual dimension to requirements analysis by displaying system relationships in spatial and graphical formats rather than traditional tabular or textual representations. This dimensional transformation allows users to perceive complex multi-variable relationships through visual patterns, spatial arrangements, and graphical metaphors, enabling faster comprehension and decision-making while maintaining analytical depth.
3Productivity
If visual knowledge and interactive graphical interfaces are leveraged, then human analytics work is amplified, but existing systems do not exploit these capabilities
Solution Approach 1:
The patent implements a dynamic graphical interface that adapts to user interactions and system state changes. The visual representation updates in real-time as users manipulate elements, add new requirements, or modify system parameters, allowing the interface to remain versatile while continuously amplifying human analytics productivity through responsive visual feedback and interactive manipulation capabilities.
Data Source
AI summary
A collection of machine readable instructions stored in a storage medium and process for graphical modeling including defining a plurality of resources comprising a plurality of resource objects and associating attributes with said task objects; defining a plurality of tasks comprising a plurality of task objects, said task objects comprise elements, with a plurality of hierarchical elements and sub-elements, and associating attributes with said elements and sub-elements; selecting at least one cognitive model defining a human cognitive process or model; determining if at least one relationship between said plurality of task objects, resource objects, and at least one cognitive model exists; graphically associating said at least one relationship with said task object, resource, object, and at least one cognitive model element where said relationship is determined; defining attributes associated with each said graphical relationship; and generating a graphical dashboard or data output associated with said task objects, resource objects, and said cognitive model based in part on said graphical relationships.