نتایج جستجو برای: principal factors analysis

تعداد نتایج: 3693930  

Journal: :Journal of physics 2022

Abstract Banda Aceh experiences flood-related problems yearly, specifically during peak rains, which inundates several residential areas and municipal protocol roads. One of the most effective ways resolving this problem is by constructing drainage channels in settlements. However, there are various associated with using process survey, planning, construction stages. During development process,...

Journal: :Open journal of plant science 2021

The exclusive attribute of the planet earth is presence life, and remarkable trait life variety or diversity, which also known as biodiversity. As per ScienceDaily news 2020, it assessed that about 15 million distinct species are present on only 2 them presently recognized by science.

Journal: :Journal of advances in mathematics and computer science 2021

This study was conducted to evaluate some development factors in Southern Nigeria order ascertain common that explained the interrelationships among them and identify best cities for recommendation. A total sample of 250 from different states three geopolitical zones used this 11 were considered. Kaiser-Meyer-Olkin (KMO) (> 0.5) computed test sampling adequacy; Bartlett’s Test Sphericity (Si...

2003
Jong-Min Lee ChangKyoo Yoo In-Beum Lee Peter A. Vanrolleghem

In this paper, a new nonlinear process monitoring technique based upon kernel principal component analysis (KPCA) is developed. In recent years, KPCA has been emerging to tackle the nonlinear monitoring problem. KPCA can efficiently compute principal components in high dimensional feature spaces by the use of integral operator and nonlinear kernel functions. The basic idea of KPCA is to first m...

A. K. Wadhwani Manish Dubey, Monika Saraswat

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

Journal: :Analytical chemistry 2011
Victoria L Brewster Lorna Ashton Royston Goodacre

Protein-based biopharmaceuticals are becoming increasingly widely used as therapeutic agents, and the characterization of these biopharmaceuticals poses a significant analytical challenge. In particular, monitoring posttranslational modifications (PTMs), such as glycosylation, is an important aspect of this characterization because these glycans can strongly affect the stability, immunogenicity...

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