An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Semi-Automatic Generation of Competency Maps Based on Educational Data Mining
International Journal of Computational Intelligence SystemsWe propose a semi-automatic method for the generation of educational-competency maps from repositories of multiple-choice question responses, using Bayesian structural learning and data-mining techniques.
David Alfonso +2 more
doaj +1 more source
Investigating Students' Pre-University Admission Requirements and Their Correlation with Academic Performance for Medical Students: An Educational Data Mining Approach. [PDF]
Brain Sci, 2023 Qahmash A, Ahmad N, Algarni A.
europepmc +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
The use of video clickstream data to predict university students' test performance: A comprehensive educational data mining approach. [PDF]
Educ Inf Technol (Dordr), 2023 Yürüm OR +2 more
europepmc +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Advanced Intelligent Discovery, EarlyView.Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Corrigendum to ``Academic data derived from a university e-government analytic platform: An educational data mining approach'' [Data in Brief, Volume 49 (2023) /109357]. [PDF]
Data Brief, 2023 Chytas K +4 more
europepmc +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Advanced Intelligent Discovery, EarlyView.Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Predicting student specializations: a Machine Learning Approach based on Academic Performance
Je-LKS: Journal of E-Learning and Knowledge SocietyEducation is a cornerstone of societal progress, equipping people with essential skills and knowledge. In today’s dynamic global society, personalized learning experiences are crucial. Data-driven methodologies, especially Educational Data Mining (EDM),
Athanasios Angeioplastis +4 more
doaj +1 more source