Near-field microwave imaging and quantitative characterization of defects in PE pipeline by Mingshi LUO, Mengmeng ZHANG, Yang FANG

“…In order to effectively detect internal defects in polyethylene (PE) pipeline, microwave non-destructive testing technology was used to detect and quantify defects in PE pipelines.A clutter suppression imaging enhancement method based on principal component analysis (PCA) was proposed for extracting defect images from PE pipelines.Threshold segmentation techniques were used to extract defect features from the enhanced images.Experimental results demonstrate that the proposed method can effectively image PE pipelines and highlight defects.The imaging quality is superior to that of images without clutter suppression.Compared to theoretical values, the average relative error in defect localization is 2.38 mm, and the relative error in area quantification is 13.25%.…”
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Estimation of Precipitation in Tianshan Mountains Based on Topographic Factors by TANG Jian

“…Based on the precipitation data of meteorological stations and considered seventopographic factors such as longitude, latitude, elevation, slope, aspect, relief and topographicopenness as principal component analysis indicators, this paper establishes the precipitationestimation model in Tianshan Mountains by the principal-component stepwise regression method. …”
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Robust Inventory System Optimization Based on Simulation and Multiple Criteria Decision Making by Ahmad Mortazavi, Alireza Arshadi khamseh

“…For simulation model optimization, a novel multicriteria and robust surrogate model is designed based on multiple attribute decision making (MADM) method, design of experiments (DOE), and principal component analysis (PCA). This approach as a main contribution of this paper, provides a framework for robust multiple criteria decision making under uncertainty.…”
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CNN-based continuous authentication scheme for vehicular digital twin by Chengzhe LAI, Xinwei ZHANG, Guanjie LI, Dong ZHENG

“…To address vehicle identity legitimacy verification issues, a continuous authentication scheme for vehicular digital twin based on convolutional neural network (CNN) was proposed.Specifically, the digital twin was used to acquire the data collected by the vehicle sensors for training the CNN deployed on the digital twin.Then, principal component analysis was performed to select appropriate typical features for the classifier.Using the features extracted by the CNN, the one-class support vector machine (OC-SVM) classifier was trained in the registration phase and the data was classified in the authentication phase, which consequently verified the current vehicle as a legitimate or malicious vehicle.Simulation results show that the proposed scheme has outstanding advantages and outperforms the existing schemes in terms of performance and accuracy.…”
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PCA clustering algorithm for indoor positioning in WLAN by Mingji YANG, Kaiyi LIU, Dan SHAO

“…In WLAN indoor location system,aiming at the problem of time-varying characteristic of received signal strength (RSS) which reduces indoor positioning accuracy,a clustering algorithm based on principal component analysis (PCA) albino RSS was put forward.The algorithm firstly treated the RSS with PCA whitening treatment to remove the correlation and improve reliability and rationality of the cluster centers.Then,K-means clustering method was used to cluster the RSS and the clustering accuracy was improved effectively,so as to improve positioning accuracy.Experimental results show that compared with the traditional clustering algorithm without PCA,probability of positioning error within 2 meters has improved 44.8% in positioning accuracy,and the performance of positioning system has been more excellent.…”
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Effects of exogenous SLs on growth and physiological characteristics of flue-cured tobacco seedlings under different degrees of drought stress by Xiao-dong Wang, Yi-nan Zhang, Xiao-guo Wang, Ye Zhuang, Shao-hua Ge

“…The primary drought tolerance traits were identified from 29 related indicators, including agronomic traits, photosynthetic efficiency, reactive oxygen metabolism, antioxidant enzyme activities, osmotic regulators, and hormone regulation, using affiliation function, principal component analysis, and cluster analysis to categorize the traits. …”
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Pengaruh Faktor Emosional Pengguna Terhadap Kesesuaian User Interface pada Sistem Informasi Benih Induk Jeruk di Balitjestro Menggunakan Kansei Engineering by Sobirin Nurfauzi, Akhmad Adi Sulianto, Sandra Malin Sutan, Agus Sugiyatno

“…Tahapan penelitian ini terdiri dari dua tahapan, yaitu merancang sistem informasi manajemen benih jeruk dan merancang tiga contoh desain tampilan menggunakan kuesioner ke 34 konsumen yang tersebar di beberapa daerah di Indonesia (petani atau penangkar dan kantor dinas) dan 14 pegawai di Balitjestro kemudian dianalisis menggunakan statistik multivariat yaitu Coefficient Correlation Analysis, Cronbach’s Alpha, Principal Component Analysis dan Factor Analysis. Hasil pengujian nilai Cronbach’s Alpha dan Factor Analysis telah memenuhi syarat minilam >0,7 dengan nilai sebesar 0.981 dan 0,8 untuk emotion “Mewah”. …”
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Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke by Ioannis Doumas, Thierry Lejeune, Martin Edwards, Gaëtan Stoquart, Yves Vandermeeren, Bruno Dehez, Stephanie Dehem

“…Relationships between clinical and robotic assessment scores with respective task-difficulty parameters were analyzed using a multivariate regression model and a principal component analysis. Results Game difficulty rapidly (within approximately thirty minutes) auto-adapted to match individual impairment levels. …”
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Unpacking the Role of Socioeconomic Factors in Insurance Inclusion: Evidence from The E-7 Countries by Berna Doğan Başar, İbrahim Halil Ekşi, Emrah Doğan

“…In this study, the socioeconomic factors determining the insurance inclusion variable, constructed using principal component analysis, were tested using the Parks-Kmenta estimator and quantile regression for the E7 countries. …”
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EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS by Bruno José Chiaramonte de Castro, Andre Bernardo

“…The aim of this work was to identify industrial process variables that presented the greatest impacts on the quantity and quality of the produced sugar, by applying principal component analysis (PCA) and partial least squares regression (PLS) to the process data of a sugar and ethanol industry. …”
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Fault analysis and research of wireless sensor network based on kernel partial least squares by Guang-hai ZHOU, Zhao-long NING, Zhi-kui CHEN, Hua ZHONG, Yue-ming HU

“…With the development of intelligent and networked sensor technology,wireless sensor networks were widely used in human life and commercial fields,because wireless sensor network nodes usually only carry limited resources,it is prone to failures due to insufficient resources,the accurate and timely fault diagnosis of WSN nodes can ensure the reliability of information,thus improving the maintainability of WSN and prolonging the service life of WSN.A method of using kernel partial least squares has been proposed to predict the fault reasons,the method overcomes the defects of traditional linear regression method and the nonlinear high dimensional space for data analysis.Through many experiments,the method can absorb the characteristics of canonical correlation analysis and principal component analysis method,provide a more thorough and rich content analysi,that the reason of the fault can be predicted effectively.…”
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Cascade Support Vector Machines with Dimensionality Reduction by Oliver Kramer

“…We analyze and compare various instantiations of dimensionality reduction preprocessing and cascade SVMs with principal component analysis, locally linear embedding, and isometric mapping. …”
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Research of Fault Diagnosis Method of Rolling Bearing based on Projection Image Analysis of Intrinsic Mode Function by Huang Xuemei

“…Finally,the feature dimension is compressed and combined based on the principal component analysis. The Support Vector Machine（ SVM） is used to realize the fault diagnosis of rolling bearing. …”
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Optimization design and application of library face recognition access control system based on improved PCA. by Na Lin, Yan Ding, Yulei Tan

“…To solve this problem, an improved method combining the Aggregating Spatial Embeddings for Face Recognition (ASEF) algorithm and Principal Component Analysis (PCA) is proposed. The PCA algorithm is optimized by introducing beta prior and full probability Bayesian model. …”
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Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images by R. Youmaran, A. Adler

“…An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA-) and Independent-Component Analysis- (ICA-) based feature decomposition schemes. …”
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Fault Feature Research of Rolling Bearing based on Empirical Mode Decomposition and Principle Component Analysis by Zheng Xin

“…It is proposed that a fault diagnosis method for rolling bearing based on empirical mode decomposition（ EMD） and multivariate statistical process control（ MSPC）,the Hilbert- Huang transformation and principal component analysis（ PCA） are combined effectively in this method. …”
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Direct Analysis of Pharmaceutical Drugs Using Nano-DESI MS by Carlos Cardoso-Palacios, Ingela Lanekoff

“…Both the active pharmaceutical ingredients (APIs) and some excipients were detected in all analyzed tablets. Principal component analysis was used to analyze mass spectral features from different tablets showing strong clustering between tablets with different APIs. …”
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The Impact of Workforce Skills on the Choice of Location of Enterprises from the Business Process Outsourcing/ Shared Service Center Sector by Tomasz Kijek, Katarzyna Budzyńska

“…The research sample consisted of 58 enterprises. The principal component analysis and the linear regression were used to conduct analyses. …”
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Design Mode Analysis of Pareto Solution Set for Decision-Making Support by Satoru Hiwa, Tomoyuki Hiroyasu, Mitsunori Miki

“…This study proposes a decision-making support methodology named design mode analysis, which consists of data clustering and principal component analysis (PCA). A design mode is indicated by the eigenvector obtained by PCA and reveals the dominant design parameters in a given dataset. …”
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Constraints for Jaccard index-based rotational symmetry focus position in binary images by N.A. Lomov, O.S. Seredin, D.V. Liakhov, O.A. Kushnir

“…The smallest circumscribed circle or ellipse and sets of concentric circles and ellipses produced by the principal component analysis were used as the approximating figure. …”
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