IEEE

Development of a Predictive Wear Model Based on Test Data Using Machine Learning Algorithms

Abstract: This study explores the application of machine learning algorithms to predict abrasive wear based on the chemical composition and hardness of materials, validated through tests using ASTM ...
IEEE

Generalized Likelihood Ratio Test for Hyperspectral Subpixel Target Detection Based on Segmented Mixing Model

Abstract: For hyperspectral subpixel target detection tasks, conventional mixing model (CMM) is one of the most intensively used models. Despite the flexibility of CMM in terms of mixing coefficient, ...
GitHub

Adaptive Test-time Learning and Autonomous Specialization

A.T.L.A.S achieves 74.6% LiveCodeBench pass@1-v(k=3) with a frozen Qwen3-14B model on a single consumer GPU — up from 36-41% in V2 — through constraint-driven generation and self-verified iterative ...
GitHub

main_page_final.py

radial-gradient(1px 1px at 20% 15%, rgba(255,255,255,0.6) 0%, transparent 100%), radial-gradient(1px 1px at 80% 25%, rgba(255,255,255,0.4) 0%, transparent 100%), radial-gradient(1px 1px at 50% 60%, ...