Results 131 to 140 of about 851,900 (211)

Prediction of SCA Scores in Specialty Coffee Using Machine Learning. [PDF]

J Food Sci
Ferraz GR, Freitas FAO, Baldi HH, Lima NF, Rodrigues GM.   +4 more
europepmc   +1 more source

Data-driven denoising in spinal cord fMRI with principal component analysis. [PDF]

Imaging Neurosci (Camb)
Hemmerling KJ, Vigotsky AD, Glanville C, Barry RL, Bright MG.   +4 more
europepmc   +1 more source

Assessing spatial variability and source identification of heavy metals in agricultural soils: A geostatistical and multivariate analysis of coastal eastern Zhejiang, China. [PDF]

PLoS One
Ji J, Wu X.
europepmc   +1 more source

Retracted: Reducing motion artifacts in 4D MR images using principal component analysis (PCA) combined with linear polynomial fitting model.

J Appl Clin Med Phys, 2015
Yang J, Wang H, Yin Y, Li D.
europepmc   +1 more source

Dimensionality reduction of COSMO-RS molecular descriptor using functional principal component analysis (FPCA) for organic solvent mapping. [PDF]

RSC Adv
Ramirez Cardenas LE, Ouaret R, Gerbaud V, Rodriguez Donis I, Thiebaud-Roux S.   +4 more
europepmc   +1 more source

Postharvest Preservation of Red Apples Using Edible Coatings and Packaging. [PDF]

Food Sci Nutr
Azadbakht M, Torshizi MV, Khatunabadi AS, Viyarsagh FK, Akbarpour FV.   +4 more
europepmc   +1 more source

Autoencoders reveal polyunsaturated fatty acids (PUFA)-Related metabolic signature linked to cancer risk. [PDF]

EBioMedicine
Breeur M, Atkins J, Peruchet-Noray L, Bonheme L, Alcala N, Dossus L, Jenab M, Johansson M, Rinaldi S, Travis RC, Bork C, Dahm CC, Tjønneland A, Olsen A, Naudin S, Park S, Truong T, Katzke V, Le Cornet C, Schulze MB, Prada M, Sacerdote C, Bendinelli B, Agnoli C, Pasanisi F, Gálvez-Navas JM, Guevara M, Heath AK, Yarmolinsky J, Gunter MJ, Ferrari P, Smith-Byrne K, Viallon V.   +32 more
europepmc   +1 more source

Influencing Factors of Pine Wood Milling Force Based on Principal Component Analysis and Multiple Linear Regression. [PDF]

Materials (Basel)
Shen B, Buck D, Yuan Z, Zhu Z.
europepmc   +1 more source

Principal Component Analysis for any type Sequences (PCA-Seq)

Симпозиум «Математическое моделирование и высокопроизводительные вычисления в биоинформатике, биомедицине и биотехнологии», 2018
openaire   +1 more source