Results 41 to 50 of about 923,571 (196)

Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison

open access: yes, 2000
Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there is constraint logic programming which computes a solution as an answer substitution to a query containing the variables of the ...
De Mot, Emmanuel   +2 more
core   +3 more sources

Technoeconomic and sustainability analysis of batch and continuous crystallization for pharmaceutical manufacturing

open access: yesAIChE Journal, EarlyView.
Abstract In pharmaceutical industries, continuous manufacturing methods have already been well established to improve productivity and process intensification. However, to better understand the trade‐offs of continuous crystallizers over the existing batch production systems, a robust technoeconomic cost and sustainability analysis is necessary to ...
Jungsoo Rhim, Zoltan K. Nagy
wiley   +1 more source

Time Blocks Decomposition of Multistage Stochastic Optimization Problems

open access: yes, 2018
Multistage stochastic optimization problems are, by essence, complex because their solutions are indexed both by stages (time) and by uncertainties (scenarios). Their large scale nature makes decomposition methods appealing.The most common approaches are
Carpentier, Pierre   +3 more
core  

Answer Set Planning Under Action Costs

open access: yes, 2011
Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs.
Eiter, T.   +4 more
core   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang   +4 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

open access: yesAdvanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto   +3 more
wiley   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

open access: yesAdvanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen   +13 more
wiley   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced 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

Clinically Informed Intelligent Classification of Ovarian Cancer Cells by Label‐Free Holographic Imaging Flow Cytometry

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone   +11 more
wiley   +1 more source

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