Current psychological paradigms frequently conceptualize resilience as a localized neural network attribute or a capacity for rigid endurance. Observing human behavior under extreme stress parameters, however, necessitates a paradigm shift. This paper formalizes resilience as a non-linear, structural dynamic system. By mathematically defining the 'Affective Transmutation Ratio' (the interplay of sorrow and aggressive drive) and identifying the necessity of 'Adaptive Cognitive Yielding', this framework posits that ultimate adaptability is not survival through endurance, but survival through heuristic destruction. Furthermore, an integrated 5-Tier Architecture and thermodynamic principles of cognitive rumination are introduced to address existing theoretical gaps in the systems-neuroscience literature.
Narsi Regression is a theoretical framework that extends conventional machine learning by treating representation evolution as an explicit optimisation problem rather than an implicit consequence of parameter optimisation. The framework models a learner as a dynamic state consist…
This paper presents the five-property framework of matter (FC field coherence, FF field frequency, R prime field capacity, PC polymorphic coupling, B4F boundary four-forces), established on the mathematical constraints of the Field Domain Number Equation (FDNE). The framework com…
The use of Advanced Driver Assistance Systems (ADAS) heavily depends on the perception models to make real-time decisions but the traditional methods have tended to use specific confidence thresholds to make the trade-offs between missed detections and false alarms to be not opti…
Here’s a line that’s been true for a while now but that we don’t talk about enough: the oldwalls between pure mathematical analysis, numerical computation, and mechanical modelingare quietly coming down, and modern scientific machine learning is basically the wreckingball. In thi…
The integration of the Internet of Things and Artificial Intelligence into global supply chains presents significant opportunities for operational optimization. However, the computational intensity of traditional machine learning models frequently undermines corporate sustainabil…
Abstract : This paper introduces a novel architecture for intelligent systems, grounded in the natural dynamics of the information field. In this approach, the fundamental concepts of computation and learning are realized not through digital instructions, but through the intrinsi…