Results 61 to 70 of about 66,822 (262)

The Association of Physical Function With Psychosocial Patient‐Reported Outcomes in People With Systemic Lupus Erythematosus

Arthritis Care &Research, EarlyView.
Objective To evaluate how modifiable psychosocial factors and fatigue relate to physical functioning in patients with systemic lupus erythematosus (SLE). Methods In this cross‐sectional study of two demographically distinct cohorts (Approaches to Positive, Patient‐Centered Experiences of Aging with Lupus [APPEAL] and California Lupus Epidemiology Study
Mrinalini Dey, Jessica Fitzpatrick, Maria Dall'Era, Charmayne Dunlop‐Thomas, Courtney Hoge, S. Sam Lim, Patricia P. Katz, Jinoos Yazdany, Laura C. Plantinga   +8 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

A Unified Feasible SQP Framework for sparse and non-negative sparse recovery

EURASIP Journal on Advances in Signal Processing
Sparse signal recovery is a central problem in many areas, including medical imaging, remote sensing, machine learning, and data science. In many practical settings, the underlying signal is inherently non-negative, due to the physical nature of the ...
Mohammad Saeid Alamdari, Masoud Fatemi
doaj   +1 more source

A Simple Gaussian Measurement Bound for Exact Recovery of Block-Sparse Signals

Discrete Dynamics in Nature and Society, 2014
We present a probabilistic analysis on conditions of the exact recovery of block-sparse signals whose nonzero elements appear in fixed blocks. We mainly derive a simple lower bound on the necessary number of Gaussian measurements for exact recovery of ...
Zhi Han, Jianjun Wang, Jia Jing, Hai Zhang   +3 more
doaj   +1 more source

Alternating projection for sparse recovery

IET Signal Processing, 2017
Reconstructing the sparse signal from a few linear measurements has attracted increasing attentions in recent years. In this study, the authors propose the alternating projection (AP) method for sparse signal recovery with learning the sparsity of the original signal.
Tao Sun 0005, Peibing Du, Lizhi Cheng, Hao Jiang 0001   +3 more
openaire   +1 more source

Sparse Approximation and Recovery by Greedy Algorithms [PDF]

IEEE Transactions on Information Theory, 2014
We study sparse approximation by greedy algorithms. Our contribution is two-fold. First, we prove exact recovery with high probability of random $K$-sparse signals within $\lceil K(1+\e)\rceil$ iterations of the Orthogonal Matching Pursuit (OMP). This result shows that in a probabilistic sense the OMP is almost optimal for exact recovery.
Eugene D. Livshitz, Vladimir N. Temlyakov   +1 more
openaire   +2 more sources

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Sparse recovery for Earth Mover Distance [PDF]

2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A, for m « n, such that for any x, given Ax, we can recover a k-sparse approximation to x under the EMD distance.
Gupta, Rishi V., Indyk, Piotr, Price, Eric C.   +2 more
openaire   +2 more sources

Number of measurements in sparse signal recovery [PDF]

2009 IEEE International Symposium on Information Theory, 2009
6 pages, 1 figure.
Paul Tune, Sibi Raj Bhaskaran, Stephen V. Hanly   +2 more
openaire   +2 more sources

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source