Robust Diffeomorphic Mapping via Geodesically Controlled Active Shapes by Daniel J. Tward, Jun Ma, Michael I. Miller, Laurent Younes

“…The dimension of this representation is constrained using principal component analysis generated from training samples. …”
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Multi-assay assessment of cytotoxicity reveals multiple mechanisms of action in 3D microtissues by Ahbid Zein-Sabatto, Katerina St. Angelo, Samantha J. Madnick, Diane Hoffman-Kim, Jeffrey R. Morgan, Jonghwan Lee

“…Here, we introduce an innovative approach that combines data from multiple assays using a linear mixed effects regression model and principal component analysis. We explored the cytotoxic response of various assay-treatment combinations using four assays with distinct mechanisms of action and seven different treatments across three types of microtissue cultures. …”
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Rolling Bearing Diagnosis Based on Adaptive Probabilistic PCA and the Enhanced Morphological Filter by Yuanqing Luo, Changzheng Chen, Siyu Zhao, Xiangxi Kong, Zhong Wang

“…Next, in the process of processing the test signal, in order to reduce the interference problem caused by strong background noise, the probabilistic principal component analysis (PPCA) method is introduced. In the traditional PPCA method, two important system parameters (decomposition principal component k and original variable n) are usually set artificially; this will greatly reduce the noise reduction performance of PPCA. …”
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Quantitative Nondestructive Testing of Wire Rope Using Image Super-Resolution Method and AdaBoost Classifier by Jigang Li, Juwei Zhang

“…A super-resolution algorithm based on interpolation uses non-subsampled shearlet transform (NSST) combining principal component analysis (PCA) and Gaussian fuzzy logic (GFL) and fuses the data of double detection board to improve the resolution and quality of defect images. …”
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Association between prudent diet, sweet food consumption, and the risk of stress, anxiety, and depression among Indonesian students by Rohmah Mayasari Noor, Maya Shofia Naila, Anisfatus Sholihah Lini, Ruhana Amalia, Yanuar Dini Cleonara

“…Students were recruited through various social media platforms. Principal component analysis was used to determine prudent-diet and sweet food among the respondents. …”
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Image Recognition and Simulation Based on Distributed Artificial Intelligence by Tao Fan

“…We have improved the HOG feature extraction algorithm. Using principal component analysis (PCA) to perform dimensionality reduction operations on HOG features and doing distributed artificial intelligence image recognition experiments, the results show that the image detection efficiency is slightly improved, and the detection speed is also improved. …”
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The Assessment of Health Risk from Heavy Metals with Water Indices for Irrigation and the Portability of Munzur Stream: A Case Study of the Ovacık Area (Ramsar Site), Türkiye by Kutlu Banu, Sarıgül Ali

“…In Munzur Stream, the irrigation water for all stations was reported to be excellent, good and suitable in terms of SAR, Na% and MH, respectively. The principal component analysis data formed the four principal components, explaining 98.22% of the total variance. …”
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A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

“…This study presents a novel hybrid machine learning (ML) model that integrates KMeans-SMOTE (KMS) for data balancing and principal component analysis (PCA) for dimensionality reduction, evaluated using the WSN-DS and TON-IoT datasets. …”
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Phenotypic Variation in Freshwater Murrel, Channa punctatus (Bloch, 1793) from Northern and Eastern Regions of India Using Truss Analysis by Ankur Kashyap, Madhu Awasthi, Mohammad Serajuddin

“…Significant variation in the morphometric analysis was observed using the truss network and multivariate analysis of the three subpopulations of freshwater murrel, C. punctatus, from the two different regions of India. Principal component analysis accounted for a total variation of 91.95% by the first three principal components. …”
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Comparison of Machine Learning Classification Methods for Determining the Geographical Origin of Raw Milk Using Vibrational Spectroscopy by Aimen El Orche, Amine Mamad, Omar Elhamdaoui, Amine Cheikh, Miloud El Karbane, Mustapha Bouatia

“…The curse of dimensionality makes some classification methods struggle to train efficient models. Thus, principal component analysis (PCA) has been applied to create a smaller set of features. …”
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Microwave-Assisted Digestion Using Dilute Nitric Acid and Hydrogen Peroxide for Multielement Determination in Wheat Flour by ICP-MS by Ibrahim A. Alhagri, Mosa Albeshry

“…The results were also evaluated using multivariate analysis techniques: principal component analysis (PCA) and hierarchical cluster analysis (HCA).…”
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Real‐Time 3‐D Modeling of the Ground Electric Field Due To Space Weather Events. A Concept and Its Validation by Mikhail Kruglyakov, Alexey Kuvshinov, Elena Marshalko

“…The factorization of the SECS‐recovered source is then performed using the principal component analysis. Eventually, we show that the GEF computation at a given time instant on a 512 × 512 grid requires less than 0.025 s provided that GEF kernels due to pre‐selected SM are computed in advance. …”
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Study of endophytic fungi of Ipomoea pes-caprae reveals the superiority of in situ plant conservation over ex situ conservation from a mycological view by Yu-Hung Yeh, Roland Kirschner

“…In addition to yielding ca. 800 strains and over 100 morphospecies, a principal component analysis (PCA) of the distribution of the dominant fungal species showed clear differences in the composition of endophytic fungal species depending on the sampling sites. …”
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Deep learning application for stellar parameter determination: III-denoising procedure by Gebran Marwan, Bentley Ian, Brienza Rose, Paletou Frédéric

“…We constructed two denoising techniques, an autoencoder, and a principal component analysis. Using random Gaussian noise added to synthetic spectra, we have trained a neural network to derive the stellar parameters Teff{T}_{{\rm{eff}}}, logg\log g, vesini{v}_{{\rm{e}}}\sin i, ξt{\xi }_{{\rm{t}}}, and [M/H] of the denoised spectra. …”
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Foraging Preference of Pollen by Stingless Bee at Three Types of Land Use in Lombok Island by Septiantina Riendriasari, Anita Apriliani Dwi Rahayu

“…The identification of pollen showed that the favorite feed plants of Tetragonula were Bromeliaceae and Cyperaceae, while the forage preference for H. erythrogastra was Rubiaceae. The Principal Component Analysis revealed that the bees' preference was influenced by the availability of forage sources. …”
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Validity and Reliability of Agoraphobic Cognitions Questionnaire-Turkish Version by Ayþegül KART, M. Hakan TÜRKÇAPAR

“…Construct validity was evaluated by factor analysis after the Kaiser-Meyer-Olkin (KMO) and Bartlett test had been performed. Principal component analysis and varimax rotation used for factor analysis. …”
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Investigation of the Soan River Water Quality Using Multivariate Statistical Approach by Zakaullah, Naeem Ejaz

“…Multivariate statistical approaches such as the Spearman correlation coefficient, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the water quality of the Soan River based on temporal and spatial patterns. …”
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An IoT and Machine Learning-Based Model to Monitor Perishable Food towards Improving Food Safety and Quality by Amina Batool, Souvik Ganguli, Hashem Ali Almashaqbeh, Muhammad Shafiq, A. L. Vallikannu, K. Sakthidasan Sankaran, Samrat Ray, F. Sammy

“…Then, using the principal component analysis technique, features are extracted from the photos, and the images are categorized using machine learning models that have been trained. …”
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Investigation on the Binding and Conformational Change of All-trans-Retinoic Acid with Peptidyl Prolyl cis/trans Isomerase Pin1 Using Spectroscopic and Computational Techniques by GuoFei Zhu, ShaoLi Lyu, Yang Liu, Chao Ma, Wang Wang

“…Molecular dynamic simulation, principal component analysis, and free energy landscape monitored the dynamical conformational characteristics of ATRA binding to Pin1. …”
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A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants by Lijie Guo, Jianxin Kang

“…Based on hazard and operability (HAZOP) analysis, kernel principal component analysis (KPCA), wavelet neural network (WNN), and fault tree analysis (FTA), a hybrid process monitoring and fault diagnosis approach is proposed in this study. …”
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