PROBLEMS WITH SHAP AND LIME IN INTERPRETABLE AI FOR EDUCATION: A COMPARATIVE STUDY OF POST-HOC EXPLANATIONS AND NEURAL-SYMBOLIC RULE EXTRACTION

Problems With SHAP and LIME in Interpretable AI for Education: A Comparative Study of Post-Hoc Explanations and Neural-Symbolic Rule Extraction

Given that education is classified as a ‘high-risk’ domain under regulatory frameworks like the EU AI Act, ensuring accurate and trustworthy interpretability in educational AI applications is critical due to its profound impact on student learning and development.This study compares a knowledge-based artificial neural network (KBANN)

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mGluR-dependent synaptic plasticity in drug-seeking.

A primary feature of drug addiction is the compulsive use despite negative consequences.A general consensus is emerging on the capacity of addictive substances to co-opt synaptic transmission and synaptic plasticity in brain Earring circuits which are involved in reinforcement and reward processing.A current hypothesis is that drug-driven neuroadap

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Study on the lateral and torsional vibration of single rotor-system using an integrated multi-body dynamics and finite element analysis

Due to rapid development in the industry, operating speeds and eccentricity produced undesirable vibrations which may lead to damage in bearings, seals, and lubrication systems.In the proposed paper, a novel analytical method was presented using an integrated multi-body dynamics and finite element analysis to simulate the lateral and torsional vibr

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COPERNICUS BIG DATA AND GOOGLE EARTH ENGINE FOR GLACIER SURFACE VELOCITY FIELD MONITORING: FEASIBILITY DEMONSTRATION ON SAN RAFAEL AND SAN QUINTIN GLACIERS

The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes.Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glacie

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