Results 91 to 100 of about 14,038,774 (295)

From Artificial to Embodied and Physical Intelligence in Smart Manufacturing

Advanced Science, EarlyView.
Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang, Xinyu Lu, Tong Liu, Jinjie Fang, Xin Li, Siqian Wu, Liuchao Jin, Wei‐Hsin Liao, Shuyou Zhang, Jianrong Tan   +9 more
wiley   +1 more source

Modularity-based approach identifies small sets of control nodes in synthetic and biological Boolean networks

Scientific Reports
This study investigates the problem of controlling the dynamics of biological systems to achieve desired outcomes (attractors). Specifically, we describe biological systems with Boolean models, which represent the system as a network, characterize system
Fatemeh Sadat Fatemi Nasrollahi, Eli Newby, Réka Albert   +2 more
doaj   +1 more source

Analisi e controllo delle Boolean control networks [PDF]

, 2022
In questa tesi vengono analizzate le principali proprietà delle Boolean netwroks (BN) e Boolean control networks (BCN). In particolare l'attenzione sarà focalizzata sull'espressione algebrica di una BN e sullo studio della stabilità, stabilizzabilità
Sterbizzi, Riccardo
core  

nodef/extra-boolean: A collection of common boolean functions

, 2022
<p>A collection of common boolean functions.<br> <a href="https://www.npmjs.com/package/extra-boolean">Node.js</a>, <a href="https://www.npmjs.com/package/extra-boolean.web">Web</a>, <a href="https://unpkg.com ...
Subhajit Sahu, George Pickering
core   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Boolean network inference and control using metaheuristic algorithms [PDF]

, 2021
This thesis focuses on the topic of gene regulatory network inference and control based on the Boolean network model. Though investigated for decades, inferring gene regulatory networks from the experimental data remains a challenging problem in ...
Shi, Ning
core   +2 more sources

Quantum algorithms for testing and learning Boolean functions [PDF]

, 2013
We discuss quantum algorithms based on the Bernstein-Vazirani algorithm for finding which input variables a Boolean function depends on. There are 2(n) possible linear Boolean functions of n input variables; given a linear Boolean function, the Bernstein-
Floess, Dominik, Hillery, Mark, Andersson, Anna Erika Elisabeth   +2 more
core   +1 more source

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

Advanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon, Dmitri Gavrilov, Peggy O’Day, Ajith Pattammattel   +3 more
wiley   +1 more source

Evolution of control with learning classifier systems

Applied Network Science, 2018
In this paper we describe the application of a learning classifier system (LCS) variant known as the eXtended classifier system (XCS) to evolve a set of ‘control rules’ for a number of Boolean network instances.
Matthew R. Karlsen, Sotiris Moschoyiannis   +1 more
doaj   +1 more source

A Generalizable Framework for Building Executable Domain‐Specific Large Language Models Under Data Scarcity: Demonstration on Semiconductor Technology Computer‐Aided Design Simulation

Advanced Intelligent Systems, EarlyView.
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang, Zhenhua Wu, Yu Liu, Kai Chang, Shaohua Wu   +4 more
wiley   +1 more source