Results 81 to 90 of about 16,931 (262)
Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends ...
Yung‐Shun Kang +6 more
wiley +1 more source
A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
This article addresses the problem of adequate network traffic modeling. A new method is proposed that enables the generation of self-similar packet flows with an arbitrarily specified degree of self-similarity.
P.E. Pustovoitov, V.O. Kompaniets
doaj +1 more source
Progressive censoring schemes for marshall-olkin pareto distribution with applications: Estimation and prediction. [PDF]
Alshenawy R, Haj Ahmad H, Al-Alwan A.
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
A Flexible Extension of Pareto Distribution: Properties and Applications. [PDF]
Alshanbari HM +4 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Pareto distribution in virtual education: challenges and opportunities. [PDF]
Valkanas K, Diamandis P.
europepmc +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
Autonomous AI‐Driven Design for Skin Product Formulations
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal ...
J. L. Guardado +4 more
doaj +1 more source

