Results 111 to 120 of about 9,964 (262)
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
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
Evaluation of Proppant Placement Efficiency in Linearly Tapering Fractures
With growing reliance on hydraulic fracturing to develop tight oil and gas reservoirs characterized by low porosity and permeability, optimizing proppant transport and placement has become critical to sustaining fracture conductivity and production ...
Xiaofeng Sun +5 more
doaj +1 more source
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
When Biology Meets Medicine: A Perspective on Foundation Models
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
Hardware acceleration of number theoretic transform for zk‐SNARK
An FPGA‐based hardware accelerator with a multi‐level pipeline is designed to support the large‐bitwidth and large‐scale NTT tasks in zk‐SNARK. It can be flexibly scaled to different scales of FPGAs and has been equipped in the heterogeneous acceleration system with the help of HLS and OpenCL.
Haixu Zhao +6 more
wiley +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin +4 more
wiley +1 more source
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
ABSTRACT The presence of antibiotics in water not only causes environmental pollution but also increases the growth of antibiotic‐resistant bacterial genes, which pose serious threats to human beings and other water residents. Large numbers of people are reportedly affected by the resistant bacterial genes, as many broad‐spectrum antibiotics are not ...
Amir Zada, Shohreh Azizi
wiley +1 more source
Comparative histological and semi‐automated image analysis of primate lips: Masson's trichrome‐stained sagittal sections were segmented to quantify the connective tissue, adipose, and muscular components, enabling interspecific comparisons of labial architecture.
Liat Rotenstreich +5 more
wiley +1 more source

