Multivariate Analyses with Two-Step Dimension Reduction for an Association Study Between ¹¹C-Pittsburgh Compound B and Magnetic Resonance Imaging in Alzheimer’s Disease by Atsushi Kawaguchi, Fumio Yamashita

“…To study the relationship between Aβ deposition and brain structure, as determined using ¹¹C-Pittsburgh compound B (PiB) and magnetic resonance imaging (MRI), respectively, we developed a regression model with PiB and MRI data as the predictor and response variables, respectively, and proposed a regression method for studying the association between them based on a supervised sparse multivariate analysis with dimension reduction based on a composite paired basis function. …”
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FDR coding and decoding algorithm for reliable transmission in underwater acoustic network by Lijuan WANG, Xiujuan DU, Chong LI

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Research of dynamic gesture recognition based on multi-instance learning of kinematics features by Cai-qiu ZHOU, Yu-wang YANG, Hai-bo PANG

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Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation by Mikhail Arbatsky, Ekaterina Vasilyeva, Veronika Sysoeva, Ekaterina Semina, Ekaterina Semina, Valeri Saveliev, Kseniya Rubina

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A NEW FAILURE PROBABILITY COMPUTING METHOD FOR MECHANICAL COMPONENTS by ZHANG YanFang, ZHANG YanLin

Subjects: “…Univariate dimension-reduction integration…”
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Fault Identification based on Improved Supervised Orthogonal Neighborhood Preserving Embedding by Ji Yunfeng, Feng Liyuan, Kuang Liang

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MiMeJF: Application of Coupled Matrix and Tensor Factorization (CMTF) for Enhanced Microbiome-Metabolome Multi-Omic Analysis by Zheyuan Ou, Xi Fu, Dan Norbäck, Ruqin Lin, Jikai Wen, Yu Sun

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Collaborative Superpixelwised PCA for Hyperspectral Image Classification by Chao Yao, Junrui Gu, Zehua Guo, Miao Ma, Qingrui Guo, Gong Cheng

Subjects: “…Dimension reduction…”
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Adaptive Reduction of Curse of Dimensionality in Nonparametric Instrumental Variable Estimation by Ming-Yueh Huang, Kwun Chuen Gary Chan

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Estimating the visibility in foggy weather based on meteorological and video data: A Recurrent Neural Network approach by Jian Chen, Ming Yan, Muhammad Rabea Hanzla Qureshi, Keke Geng

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Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

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RESEARCH ON FAULT DIAGNOSIS METHOD BASED ON NEIGHBORHOOD ADAPTIVE LLTSA FOR DIMENSION REDUTION by XU QiongYan, WU YinHua

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TOOL WEAR STATE MONITORING BASED ON WAVELET PACKET BP＿ADABOOST ALGORITHM by ZHU Xiang, XIE Feng

Subjects: “…Kernel principal component analysis（KPCA） dimension reduction…”
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Asymptotic modeling of viscoelastic thin plates and slender beams, a unifying approach by Terapabkajornded, Yotsawat, Orankitjaroen, Somsak, Licht, Christian, Weller, Thibaut

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FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM by LU Li, CHEN Ying

“…And then use the nonlinear mapping to map the high dimension fault feature into an implicit feature space to dimension reduction. Thus a linear transformation is performed to preserve locality geometric structures of the fault feature,which solves the difficulty of parameter selection in computing affinity matrix,as a result,better fault diagnosis accuracy can achieved. …”
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An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“…In this paper, we study document clustering with the common clustering pipeline that includes vectorization with BERT or Doc2Vec, dimension reduction with PCA or UMAP, and clustering with K-Means or HDBSCAN. …”
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Improving RLRN Image Splicing Detection with the Use of PCA and Kernel PCA by Zahra Moghaddasi, Hamid A. Jalab, Rafidah Md Noor, Saeed Aghabozorgi

“…Results show that kernel PCA is a nonlinear dimension reduction method that has the best effect on R, G, B, and Y channels and gray-scale images.…”
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Dimension Estimation Using Weighted Correlation Dimension Method by Yuanhong Liu, Zhiwei Yu, Ming Zeng, Shun Wang

“…Dimension reduction is an important tool for feature extraction and has been widely used in many fields including image processing, discrete-time systems, and fault diagnosis. …”
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Gear Fault Diagnosis based on Feature Fusion and Sparse Representation by Wang Jiangping, Duan Tengfei

“…The feature fusion is implemented with KPCA,and the dimension reduction of original feature vector is used as the input of classification based on sparse representation. …”
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Kernel Sliced Inverse Regression: Regularization and Consistency by Qiang Wu, Feng Liang, Sayan Mukherjee

“…Kernel sliced inverse regression (KSIR) is a natural framework for nonlinear dimension reduction using the mapping induced by kernels. …”
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