Results 1 to 10 of about 298,220 (292)

A Feasibility Study of Three-Dimensional Empirical Orthogonal Functions From the NASA JPL Ocean General Circulation Model: Computing, Visualization and Interpretation

Tellus: Series A, Dynamic Meteorology and Oceanography, 2023
Existing oceanic studies on either data reconstruction or dynamics often used 2-dimensional empirical orthogonal functions (EOF) for sea surface temperature (SST) and for deep layers.
Danielle Lafarga, Thomas Bui, Y. Tony Song, Thomas M. Smith, Samuel S. P. Shen   +4 more
doaj   +1 more source

A Novel Error Criterion of Fundamental Matrix Based on Principal Component Analysis

Remote Sensing, 2022
Estimating the fundamental matrix (FM) using the known corresponding points is a key step for three-dimensional (3D) scene reconstruction, and its uncertainty directly affects camera calibration and point-cloud calculation.
Yuxia Bian, Shuhong Fang, Ye Zhou, Xiaojuan Wu, Yan Zhen, Yongbin Chu   +5 more
doaj   +1 more source

Overcoming floor and ceiling effects in knee arthroplasty outcome measurement: mapping the Oxford Knee Score and High Activity Arthroplasty Score onto a common scale

Bone & Joint Research, 2023
Aims: To map the Oxford Knee Score (OKS) and High Activity Arthroplasty Score (HAAS) items to a common scale, and to investigate the psychometric properties of this new scale for the measurement of knee health.
Conrad J. Harrison, Constantin Y. Plessen, Gregor Liegl, Jeremy N. Rodrigues, Shiraz A. Sabah, David J. Beard, Felix Fischer   +6 more
doaj   +1 more source

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals

Frontiers in Neuroscience, 2022
We describe and apply novel methodology for whole-brain analysis of resting state fMRI functional connectivity data, combining conventional multi-channel Pearson correlation with covariance analysis.
Abraham Z. Snyder, Abraham Z. Snyder, Tomoyuki Nishino, Joshua S. Shimony, Eric J. Lenze, Julie Loebach Wetherell, Julie Loebach Wetherell, Michelle Voegtle, J. Philip Miller, Michael D. Yingling, Daniel Marcus, Jenny Gurney, Jerrel Rutlin, Drew Scott, Lisa Eyler, Deanna Barch, Deanna Barch, Deanna Barch   +17 more
doaj   +1 more source

A comment on “Variability in plant nutrients reduces insect herbivore performance” [PDF]

Rethinking Ecology, 2019
In their recent contribution, Wetzel et al. [Wetzel et al. (2016) Variability in plant nutrients reduces insect herbivore performance. Nature 539: 425-427] predict that variance in the plant nutrient level reduces herbivore performance via the nonlinear ...
Apostolos-Manuel Koussoroplis, Toni Klauschies, Sylvain Pincebourde, David Giron, Alexander Wacker   +4 more
doaj   +3 more sources

Generalized product-sum variogram models of the data of the Center of Marine Research

Lietuvos Matematikos Rinkinys, 2004
Environmental data usually depends on both spatial and temporal components. Therefore, it is essential to have statistical models to describe how the data vary across space and time.
Ingrida Krūminienė, Kęstutis Dučinskas   +1 more
doaj   +3 more sources

Femtosecond covariance spectroscopy [PDF]

Proceedings of the National Academy of Sciences, 2019
Significance Here we establish femtosecond covariance spectroscopy as a technique that uses ultrashort stochastic light pulses to measure nonlinear material responses. By using pulses with spectrally uncorrelated fluctuations we can leverage on the noise and consider each repetition of the experiment as a measurement under different ...
TOLLERUD, JONATHAN OWEN, SPARAPASSI, GIORGIA, MONTANARO, ANGELA, Asban, Shahaf, Glerean, Filippo, Giusti, Francesca, Marciniak, Alexandre, Kourousias, George, Billè, Fulvio, Cilento, Federico, Mukamel, Shaul, Fausti, Daniele   +11 more
openaire   +6 more sources

Covariance-insured screening [PDF]

Computational Statistics & Data Analysis, 2019
Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors far greater than the sample size. In order to identify more novel biomarkers and understand biological mechanisms, it is vital to detect signals weakly associated with outcomes among ultrahigh-dimensional predictors.
Kevin He, Jian Kang, Hyokyoung G. Hong, Ji Zhu, Yanming Li, Huazhen Lin, Han Xu, Yi Li   +7 more
openaire   +3 more sources

Statut de la langue française au Maroc : didactique et représentations

Revue des Langues, Cultures et Sociétés, 2015
Dans cet article, il s’agit de mener une réflexion sur les enjeux actuels de l’enseignement/apprentissage des langues étrangères, en particulier  la question de la langue française dans le système éducatif marocain. Une étude qui se fera au croisement de
Amal SADIQ
doaj   +1 more source

Covariance of Covariance Features for Image Classification [PDF]

Proceedings of International Conference on Multimedia Retrieval, 2014
In this paper we propose a novel image descriptor built by computing the covariance of pixel level features on densely sampled patches and encoding them using their covariance. Appropriate projections to the Euclidean space and feature normalizations are employed in order to provide a strong descriptor usable with linear classifiers. In order to remove
SERRA, GIUSEPPE, GRANA, Costantino, MANFREDI, MARCO, CUCCHIARA, Rita   +3 more
openaire   +2 more sources