Classification of different types of cloud images is the primary issue used to forecast precipitation and other weather constituents. A PCA based classification system has been presented in this paper to classify the different types of single-layered and multi-layered clouds. Principal Component Analysis (PCA) provides enhanced accuracy in features based image identification and classification ...

spatial patterns are useful descriptors of the horizontal structure in a plant population and may change over time as the individual components of the population grow or die out. but, whether this is the case for desert woody annuals is largely unknown. in the present investigation, the variations in spatial patterns of tribulus terrestris during different pulse events in semi-arid area of the ...

Commercial herbal preparations are typically very complex mixtures and the relationship between content of various constituents and pharmacological action of the formulation is usually unclear. Such formulations are nevertheless standardized using a single marker constituent or a group of closely related constituents, which provides no information about other abundant constituents present in th...

In this project you will explore the use of Principle Component Analysis (PCA) and Probabilistic PCA (PPCA). PPCA is closely-related to factor analysis, which is described in chapter 14 of your text. Our application is face recognition, following on the work of Moghadden and Pentland. A minimum version of this project would involve reading chapter 14 and conducting a face recognition experiment...

Purpose: To study the influence of different sulfur fumigation time and dosage on the chemical constituents of Baizhi (Angelicae dahurica Radix). Methods: The relationship of chemical constituents in Baizhi with different sulfur fumigation time and dosages was evaluated by high performance liquid chromatography (HPLC) fingerprint and chemometrics methods, including similarity analysis (SA), hie...

Qingwen Baidu Decoction (QBD) is an extraordinarily "cold" formula. It was traditionally used to cure epidemic hemorrhagic fever, intestinal typhoid fever, influenza, sepsis and so on. The purpose of this study was to discover relationships between the change of the constituents in different extracts of QBD and the pharmacological effect in a rat model of acute lung injury (ALI) induced by lipo...

Principal Component Analysis (PCA) is the most widely used unsupervised dimensionality reduction approach. In recent research, several robust PCA algorithms were presented to enhance the robustness of PCA model. However, the existing robust PCA methods incorrectly center the data using the `2-norm distance to calculate the mean, which actually is not the optimal mean due to the `1-norm used in ...

Principal component analysis (PCA) is an unsupervised method for learning low-dimensional features with orthogonal projections. Multilinear PCA methods extend PCA to deal with multidimensional data (tensors) directly via tensor-to-tensor projection or tensor-to-vector projection (TVP). However, under the TVP setting, it is difficult to develop an effective multilinear PCA method with the orthog...

Principal component analysis (PCA) is possibly one of the most widely used statistical tools to recover a low rank structure of the data. In the high-dimensional settings, the leading eigenvector of the sample covariance can be nearly orthogonal to the true eigenvector. A sparse structure is then commonly assumed along with a low rank structure. Recently, minimax estimation rates of sparse PCA ...