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Sensors, 2022 Programming is a skill that requires high levels of logical thinking and problem-solving abilities. According to the Curriculum Guidelines for the 12-Year Basic Education currently implemented in Taiwan, programming has been included in the mandatory ...
Chi-Yi Tsai, Yu-Cheng Lai
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Brain Sciences, 2021 It is widely acknowledged that obesity is a growing public clinical issue involving both physical and psychological well-being. Nevertheless, the relationship between psychological features and weight gain is still unclear. Although emotional eating (EE)
Ines Villano +11 more
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BCCT: A GUI Toolkit for Brain Structural Covariance Connectivity Analysis on MATLAB
Frontiers in Human Neuroscience, 2021 Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders.
Qiang Xu +18 more
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Large Covariance Estimation by Thresholding Principal Orthogonal Complements [PDF]
, 2013 This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-
Fan, Jianqing +2 more
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Robustness of analysis of covariance (ancova) under the distributions assumptions and variance homogeneity [PDF]
Eurasian Journal of Veterinary Sciences, 2020 Aim: As in all parametric methods, the ANCOVA method assumes that normal distributions of errors, homogeneity of variances, and error terms are independent of each other. However, unusual distributions in practice are more common than normal distribution.
Can Ateş +3 more
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Performance of internal Covariance Estimators for Cosmic Shear Correlation Functions [PDF]
, 2015 Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two ...
Eifler, T. F. +3 more
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Bayesian Sparse Factor Analysis of Genetic Covariance Matrices [PDF]
, 2013 Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms ...
Mukherjee, Sayan, Runcie, Daniel E
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Implementing Quantitative Literacy at Southwestern Community College, North Carolina
Numeracy, 2015 There is a time when articulation agreements between universities and community colleges come to an end. When this happened in North Carolina, there was great hope that not only would the mathematics classes that were offered in the North Carolina ...
Vicki Todd, John Wagaman
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Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices [PDF]
, 2015 This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection.
Cai, Tony, Ma, Zongming, Wu, Yihong
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IPCO: Inference of Pathways from Co-variance analysis
BMC Bioinformatics, 2020 Background Key aspects of microbiome research are the accurate identification of taxa and the profiling of their functionality. Amplicon profiling based on the 16S ribosomal DNA sequence is a ubiquitous technique to identify and profile the abundance of ...
Mrinmoy Das +2 more
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