Results 61 to 70 of about 27,852 (244)

Real‐time fault detection in multicomponent nuclear‐waste slurries through data fusion of spectroscopic sensors

open access: yesAIChE Journal, EarlyView.
Abstract Three instruments–Raman spectroscopy, attenuated total reflectance–Fourier transform infrared spectroscopy, and focused beam reflectance measurement–were used to detect sensor faults, mixing faults, and unanticipated chemistry in a system of multicomponent slurries.
Steven H. Crouse   +2 more
wiley   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

open access: yesAIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed   +4 more
wiley   +1 more source

Sea Clutter Suppression Method Based on Correlation Features

open access: yesJournal of Marine Science and Engineering
Radar target detection in a sea clutter environment is of significant importance in both civilian and military applications, with the detection of small maneuvering targets being particularly challenging.
Zhen Li   +5 more
doaj   +1 more source

On subspace-diskcyclicity

open access: yesArab Journal of Mathematical Sciences, 2017
In this paper, we define and study subspace-diskcyclic operators. We show that subspace-diskcyclicity does not imply diskcyclicity. We establish a subspace-diskcyclic criterion and use it to find a subspace-diskcyclic operator that is not subspace ...
Nareen Bamerni, Adem Kılıçman
doaj   +1 more source

A rough set based subspace clustering technique for high dimensional data

open access: yesJournal of King Saud University: Computer and Information Sciences, 2020
Subspace clustering aims at identifying subspaces for cluster formation so that the data is categorized in different perspectives. The conventional subspace clustering algorithms explore dense clusters in all the possible subspaces.
B. Jaya Lakshmi, M. Shashi, K.B. Madhuri
doaj   +1 more source

Subspace evasive sets

open access: yesProceedings of the forty-fourth annual ACM symposium on Theory of computing, 2012
In this work we describe an explicit, simple, construction of large subsets of F^n, where F is a finite field, that have small intersection with every k-dimensional affine subspace. Interest in the explicit construction of such sets, termed subspace-evasive sets, started in the work of Pudlak and Rodl (2004) who showed how such constructions over the ...
Dvir, Zeev, Lovett, Shachar
openaire   +2 more sources

Detecting Fourier Subspaces [PDF]

open access: yesJournal of Fourier Analysis and Applications, 2015
Let G be a finite abelian group. We examine the discrepancy between subspaces of l^2(G) which are diagonalized in the standard basis and subspaces which are diagonalized in the dual Fourier basis. The general principle is that a Fourier subspace whose dimension is small compared to |G| = dim(l^2(G)) tends to be far away from standard subspaces.
Akemann, Charles, Weaver, Nik
openaire   +3 more sources

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren   +10 more
wiley   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah   +3 more
wiley   +1 more source

A NEW REPRESENTATION RESULT FOR STOCHASTIC DIFFERENTIAL EQUATIONS WITH INFINITE MARKOV JUMPS AND MULTIPLICATIVE NOISE [PDF]

open access: yesFiabilitate şi Durabilitate, 2012
In this paper we give a new representation of the conditional mean square of the solutions for a classof stochastic differential linear equations with infinite Markov jumps (SDELMs) and multiplicative noise. Theobtained result is related to the solutions
Viorica Maria Ungureanu
doaj  

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