ABSTRACT This study examines the environmental, social and governance (ESG) scoring methodologies used by Bloomberg and S&P Global through the lens of Data Envelopment Analysis (DEA). It addresses a notable gap in the literature by identifying the underlying factors that shape ESG scores and providing practical insights for companies seeking to ...
Philipe Balan +4 more
wiley +1 more source
Application of SVM and SVD Technique Based on EMD to the Fault Diagnosis of the Rotating Machinery
Targeting the characteristics that periodic impulses usually occur whilst the rotating machinery exhibits local faults and the limitations of singular value decomposition (SVD) techniques, the SVD technique based on empirical mode decomposition (EMD) is ...
Junsheng Cheng +3 more
doaj +1 more source
Transformation of Non-Euclidean Space to Euclidean Space for Efficient Learning of Singular Vectors
Singular value decomposition (SVD) is a popular technique to extract essential information by reducing the dimension of a feature set. SVD is able to analyze a vast matrix in spite of a relatively low computational cost.
Seunghyun Lee, Byung Cheol Song
doaj +1 more source
Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T1, T2, and M0 Mapping
ABSTRACT Background 0.55T systems offer unique advantages and may support expanded access to cardiac MRI. Purpose To assess the feasibility of 0.55T cardiac MR Fingerprinting (MRF), leveraging a deep image prior reconstruction to mitigate noise. Study Type Phantom and prospective in vivo assessment.
Zhongnan Liu +9 more
wiley +1 more source
Unraveling complexity: Singular value decomposition in complex experimental data analysis
Analyzing complex experimental data with multiple parameters is challenging. We propose using Singular Value Decomposition (SVD) as an effective solution.
Judith F. Stein, Aviad Frydman, Richard Berkovits
doaj +1 more source
A MR Fingerprinting Development Kit for Quantitative 3D Brain Imaging
ABSTRACT Background Magnetic resonance fingerprinting (MRF) is an emerging quantitative imaging technique that enables multiparametric tissue characterization, but its adoption has been hindered by the complexity of data acquisition and post‐processing. These technical and implementation challenges have limited its broader clinical deployment.
Rasim Boyacioglu +11 more
wiley +1 more source
An Enhanced Incremental SVD Algorithm for Change Point Detection in Dynamic Networks
Change point detection is essential to understand the time-evolving structure of dynamic networks. Recent research shows that a latent semantic indexing (LSI)-based algorithm effectively detects the change points of a dynamic network.
Yongsheng Cheng, Jiang Zhu, Xiaokang Lin
doaj +1 more source
Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends
Using nearly four decades of Meteosat satellite data (1983–2020), this study presents a country‐wide climatology of sunshine duration (SDU) in Brazil. The results reveal marked regional contrasts, dominant modes of variability, and significant long‐term trends, providing new information on the most relevant meteorological systems that influence SDU and
Maria Lívia Lins Mattos Gava +2 more
wiley +1 more source
Comparative Study of SVD and QRS in Closed-Loop Beamforming Systems
We compare two closed-loop beamforming algorithms, one based on singular value decomposition (SVD) and the other based on equal diagonal QR decomposition (QRS).
Sun, Sumei, Yuen, Chau, Zhang, Jian-Kang
core +1 more source
Frozen Differential Scattering in Reconfigurable Complex Media
A localized perturbation universally results in a rank‐one update of the scattering matrix of any complex medium. The resulting differential output wavefront is “frozen”: its spatial pattern is fixed (agnostic to the input wavefront). Experiments with a programmable‐metasurface‐parametrized wireless link validate frozen differential scattering and ...
Philipp del Hougne
wiley +1 more source

