Results 31 to 40 of about 31,195 (250)

A Modified Singular Value Decomposition (MSVD) Approach for the Enhancement of CCTV Low-Quality Images

IEEE Access
Image enhancement and reconstruction is an important field of research in digital image analysis. To increase the quality of low-contrast images, a variety of image-enhancing technologies are available.
Shahzada Fahad, Sami Ur Rahman, Fakhre Alam, Muhammad Yousaf, Faten S. Alamri, Naveed Abbas, Saeed Ali Bahaj, Amjad R. Khan   +7 more
doaj   +1 more source

Feature extraction of vibration signal of roadheader based on singular value decompositio

Gong-kuang zidonghua, 2019
In view of difficulty of dynamic load identification of roadheader, feature extraction method of vibration signal of roadheader based on singular value decomposition was proposed.
ZHANG Linfeng, TIAN Muqin, SONG Jiancheng, HE Ying, FENG Junling, YANG Xiang   +5 more
doaj   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Singular Value Decomposition Wavelength-Multiplexing Ghost Imaging

Photonics
To enhance imaging quality, singular value decomposition (SVD) has been applied to single-wavelength ghost imaging (GI) or color GI. In this paper, we extend the application of SVD to wavelength-multiplexing ghost imaging (WMGI) for reducing the ...
Yingtao Zhang, Xueqian Zhang, Zongguo Li, Hongguo Li   +3 more
doaj   +1 more source

Singular Value Decomposition and Ligand Binding Analysis

Journal of Spectroscopy, 2013
Singular values decomposition (SVD) is one of the most important computations in linear algebra because of its vast application for data analysis. It is particularly useful for resolving problems involving least-squares minimization, the determination of
André Luiz Galo, Márcio Francisco Colombo   +1 more
doaj   +1 more source

Singular Value Decomposition [PDF]

, 2011
While the eigenvalue decomposition \({\bf A} = \bf T{\bf \Lambda}T^{\prime},\) say, concerns only symmetric matrices, the singular value decomposition (SVD) \({\bf A} = \bf U{\bf \Delta}V^{\prime},\) say, concerns any n × m matrix. In this chapter we illustrate the usefulness of the SVD, particularly from the statistical point of view.
Simo Puntanen, George P. H. Styan, Jarkko Isotalo   +2 more
openaire   +2 more sources

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Differentiable Singular Value Decomposition

CoRR
Singular value decomposition is widely used in modal analysis, such as proper orthogonal decomposition and resolvent analysis, to extract key features from complex problems. SVD derivatives need to be computed efficiently to enable the large scale design optimization.
Rohit Kanchi, Sicheng He
openaire   +2 more sources

Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini, Alessia Casarini, Niccolò Biagioli, Laura Mirandola, Daniela Ballotta, Paul Summers, Simona Scolastico, Laura Madrassi, Maurilio Genovese, Marcella Malagoli, Gaetano Cantalupo, Giada Giovannini, Matteo Pugnaghi, Niccolò Orlandi, Laura Tassi, Valeria Cuccarini, Domenico Aquino, Elena Tartara, Fulvia Palesi, Giuseppe Didato, Paolo Vitali, the 3TLE Study Group, Roberta Di Giacomo, Fabio Doniselli, Federica Mazzi, Carlo Andrea Galimberti, Claudia A. M. Gandini Wheeler‐Kingshott, Stefano Meletti, Anna Elisabetta Vaudano   +28 more
wiley   +1 more source