The Role of Aquaculture in Shaping the Morphology of <i>Babylonia areolata</i>: A Comparative Study of Cultured and Wild Populations by Haishan Wang, Zhi Chen, Yuhe Tong, Le Ye, Youming Li

“…Statistical methods, including Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), were used to assess morphological differences. …”
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Establishment of fingerprint of phenolic compounds in Semen Ziziphi Spinosae and study on the spectrum-effect relationship based on different preceding cropping areas by Junfeng Jiang, Jun Luo, Wenyu Zheng, Jiayi Liu, Hui Jiang, Cuiyun Wu, Hongjin Bai

“…The 22 SZS samples could be categorized into 3 groups, with cluster analysis and principal component analysis results being largely consistent. …”
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Thriving in golden years: Promoting psychological well-being for healthy ageing in India by Dhananjay W Bansod, Raghunath Mandi

“…Methods: We created composite score of healthy ageing using Principal Component Analysis based on LASI (wave-1) data 2017–18 in accordance with the WHO framework of healthy ageing based on the functional ability of an individual. …”
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Fluorescence Characteristics of Humic Acid in Chinese Black Soil under Long-Term Fertilization by Dan Wei, Yan Li, Shan-shan Cai, Liang Jin, Yu-mei Li, Wei Wang, Yang Bai, Yu Hu, Nicholas Clarke

“…Excitation and emission matrices combined with parallel factor analysis were used to investigate the structure of the humic acid. Principal component analysis was performed to select the most suitable parameters for the description of humic acid. …”
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Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation by Xiaoming Zhang, Lean Yu, Hang Yin

“…The experimental results demonstrated that the proposed domain-adaptation-based multistage ensemble learning paradigm is superior to principal component analysis, joint distribution adaptation, random forest, and other ensemble and transfer learning methods. …”
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Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing by Hongwei Song, Ming Li, Chaoquan Wu, Qingchuan Wang, Shunke Wei, Mingxing Wang, Wenhui Ma

“…Then, the transducer signal is preprocessed by distance correlation analysis (DCA), and independent features are extracted by principal component analysis (PCA). The extracted features are used as input to a least-squares fit, which gave the oil flow rates as output. …”
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Microcrustaceans structure determined by the type and trophic state of lakes by Bharguan Pizzol Nogueira, Camila Moreira-Silva, Thaís Coimbra Marigo, Gilmar Perbiche-Neves

“…Results A principal component analysis (PCA) separated three types of lakes: eutrophic (natural and man-made) to mesotrophic. …”
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Changes in Vitamin E and β-Carotene Contents in Various Edible Cassava Leaves (Manihot esculenta Crantz) of Different Ages across Multiple Seasons by Alphonse Laya, Benoît B. Koubala

“…The effects of varieties and harvest ages on the biosynthesis regulation of these compounds were confirmed by principal component analysis (F1x F2: 74.34%). Edible cassava leaves can be considered as sources of vitamin E for natural dietary antioxidant during different ages, and the best time to harvest EN and AD varieties is at 6MAP on the basis of α-tocopherol equivalent or content of biologically active vitamin E content, and EN and AD varieties performed the overall best. …”
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Phenotypic Diversity of Doum Palm (Hyphaene compressa), a Semi‐Domesticated Palm in the Arid and Semi‐Arid Regions of Kenya by Agnes Omire, Nancy L. M. Budambula, Johnstone Neondo, Robert Gituru, Cecilia Mweu

“…Linear mixed-effects models, principal component analysis, and linear discriminant analyses were used to assess the variation in the morphological traits of doum palm based on the regions. …”
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PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs by Roberto Opromolla, Giancarmine Fasano, Michele Grassi, Al Savvaris, Antonio Moccia

“…Instead, line fitting is carried out by exploiting the Principal Component Analysis, unlike traditional techniques relying on least squares linear regression. …”
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An Adaptive EEG Feature Extraction Method Based on Stacked Denoising Autoencoder for Mental Fatigue Connectivity by Zhongliang Yu, Lili Li, Wenwei Zhang, Hangyuan Lv, Yun Liu, Umair Khalique

“…Compared with principal component analysis, the proposed method can significantly improve the signal to noise ratio and suppress the noise interference. …”
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INTERSTRAIN DIFFERENCES IN EMOTIONAL AND WEIGHT INDICES IN GC RATS WITH CATATONIC RESPONSE AND WISTAR RATS by T. A. Alekhina, R. V. Kozhemjakina

“…Multivariate analysis methods were applied: factor analysis and principal component analysis. We confirmed the inclination of GC rats of the generation studied to freezing in quiet surrounding and after a strong acoustic sti - mulus. …”
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Baseline hydro-geochemical characteristics of groundwater in Abu Ali watershed (Northern Lebanon) by Rachad Al Haj, Mohammad Merheb, Jalal Halwani, Baghdad Ouddane

“…Additionally, cluster analysis and principal component analysis (PCA) divide the samples into four groups. …”
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Re-calibrating measurements of low-cost air quality monitors using PCR-GPR air quality forecasting models. by Bing Liu, Shuting Yang, Junqi Wang

“…First, we perform Principal Component Analysis (PCA) on the measurement data of the AQM to solve the multicollinearity problem. …”
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Adaptive Gaussian Incremental Expectation Stadium Parameter Estimation Algorithm for Sports Video Analysis by Lizhi Geng

“…Also, different online updating strategies are adopted for the template set and Principal Component Analysis (PCA) subspace to alleviate the drift problem while ensuring that the algorithm can adapt to the changes of target appearance in the dynamic tracking environment. …”
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Fifth Lumbar Vertebral Shape in Early-Stage Lumbar Spondylolysis: Three-Dimensional Bone Morphology Analysis Using Homologous Models by Yuji Yamane, Hajime Toda, Masaki Katayose

“…Methods: Homologous models of the L5 vertebra were constructed using computed tomography data from 72 patients with early-stage spondylolysis (SP group) and 95 patients without spondylolysis (CON group). Principal component analysis was performed on the three-dimensional coordinates of all vertices of the generated homologous models. …”
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PTR-ToF-MS VOC Profiling of Raw and Cooked Gilthead Sea Bream Fillet (<i>Sparus aurata</i>): Effect of Rearing System, Season, and Geographical Origin by Iuliia Khomenko, Valentina Ting, Fabio Brambilla, Mirco Perbellini, Luca Cappellin, Franco Biasioli

“…A total of 227 mass peaks were identified. Principal component analysis (PCA) showed a clear separation between cooked and raw samples, with cooking causing a significant increase in 64% of VOCs, especially hydrogen sulphide, methanethiol, and butanal. …”
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Fault Diagnosis of Planetary Gearbox Based on Motor Current Signal Analysis by Ziyuan Jiang, Qinkai Han, Xueping Xu

“…Subsequently, four classical machine learning models, including the support vector machine (SVM), decision tree (DT), random forest (RF), and AdaBoost, are used for fault classifications based on the features extracted via principal component analysis (PCA). The convolutional neural network (CNN), which can automatically extract features, is also adopted. …”
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Comparative Performance of Sentinel-2 and Landsat-9 Data for Raw Materials’ Exploration Onshore and in Coastal Areas by Morgana Carvalho, Joana Cardoso-Fernandes, Francisco Javier González, Ana Claudia Teodoro

“…Standard remote sensing methods such as RGB combinations, Principal Component Analysis (PCA), and band ratios were adapted and compared for both satellites. …”
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Wheat cultivars grain yield and quality traits variability under conditions of southern Pannonian plain by Timić Jovana, Dražić Tanja, Mirosavljević Milan, Jocković Bojan, Aćin Vladimir, Mikić Sanja, Brbaklić Ljiljana

“…Thousand grain weight showed the highest variability depending on genotype influence, protein content and sedimentation value that were mostly affected by environmental conditions, while the genotype and environment interaction had the greatest impact on hectoliter weight and grain yield. Using principal component analysis significant positive relationship was observed between protein content and sedimentation value, and between thousand grain weight and hectoliter weight. …”
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