Results 81 to 90 of about 1,590 (175)

Excitation Emission Matrix and Parallel Factor Analysis of Blood Plasma for Effective Delineation of Potentially Malignant Disorders

Journal of Indian Academy of Oral Medicine and Radiology
Background: Native fluorescence spectroscopy is a noninvasive real-time tool to probe the molecular alteration in tissues in pathological conditions by utilizing fluorescence properties of intrinsic fluorophores.
Pravda Chidambaranathan, Rajvikram Natarajan, Divyambika Catakapatri Venugopal, Saravanan Ramachandran, Jamal Mohamed Thoufeeq, Singaravelu Ganesan   +5 more
doaj   +1 more source

Novel method based on fractional lower-order correntropy-analogous statistics for parameter jointly estimation in bistatic MIMO radar

Tongxin xuebao, 2016
According to the performance degradation problem of parameter estimation algorithm in the Alpha stable dis-tribution noise, inspired by the concept of correntropy, a new class of statistics, namely, the fractional lower-order cor-rentropy-analogous ...
Li LI, Tian-shuang QIU, Ming-yan HE
doaj   +2 more sources

Dissolved Organic Matter Behaviour by Conventional Treatments of a Drinking Water Plant: Controlling Its Changes with EEM-PARAFAC

Applied Sciences
In the last 20 years, several articles related to the use of fluorescence excitation–emission matrices—parallel factor analysis (EEM-PARAFAC) to monitor dissolved organic matter (DOM) in drinking- and wastewater treatment plants were published ...
Iván Sciscenko, Rita Binetti, Carlos Escudero-Oñate, Isabel Oller, Antonio Arques   +4 more
doaj   +1 more source

Latent Functional PARAFAC for Modeling Multidimensional Longitudinal Data

Psychometrika
Abstract In psychometric sciences, such as social or behavioral sciences, and, similarly, in medical sciences, it is increasingly common to deal with longitudinal data organized as high-dimensional multidimensional arrays, also known as tensors.
Sort, Lucas, Brusquet, Laurent Le, Tenenhaus, Arthur   +2 more
openaire   +3 more sources

Decoding SSVEP Responses based on Parafac Decomposition.

, 2012
In this position paper, we investigate whether a parallel factor analysis (Parafac) decomposition is beneficial to the decoding of steady-state visual evoked potentials (SSVEP) present in electroencephalogram (EEG) recordings taken from the subject's scalp.
Manyakov, Nikolay V., Chumerin, Nikolay, Combaz, Adrien, Robben, Arne, van Vliet, Marijn, Van Hulle, Marc   +5 more
openaire   +1 more source

A Fluorescence-Based Sensor Combined with Chemometric and Deep Learning Approaches for Detecting and Quantifying Coconut Milk Fraud in Bovine Milk. [PDF]

Sensors (Basel)
Cahyarani SMD, Lee H.
europepmc   +1 more source

Bayesian Tensor Decomposition for Clustering Latent Symptom Profiles for Verbal Autopsy Data. [PDF]

Stat Med
Zhu Y, Li ZR.
europepmc   +1 more source

Enhancing Soil Water-Soluble Carbon Stability Structure Through Straw Return in Maize-Soybean Rotation in Mollisols. [PDF]

Plants (Basel)
Kuang E, Liu L, Wang Z, Zhang J, Zhu Y, Zhu D, Colinet G, Guo B, Sun L.   +8 more
europepmc   +1 more source

PARAFAC-SPARK: Parallel tensor decompositions on spark

, 2019
Tensors are higher order matrices, widely used in many data science applications and scienti c disciplines. The Canonical Polyadic Decomposition (also known as CPD/PARAFAC) is a widely adopted tensor factorization to discover and extract latent features of tensors usually applied via alternating squares (ALS) method.
openaire   +2 more sources

Extraction method shapes soil water-soluble organic matter composition as revealed by absorbance, fluorescence, and parallel factor analysis (PARAFAC). [PDF]

Sci Rep
Fasching C, Boodoo KS, Feld-Golinski A, Foroushani MA, Chifflard P.   +4 more
europepmc   +1 more source