Stage-Based Remaining Useful Life Prediction for Bearings Using GNN and Correlation-Driven Feature Extraction by Guangzhong Huang, Wenping Lei, Xinmin Dong, Dongliang Zou, Shijin Chen, Xing Dong

“…First, the proposed Pearson–Spearman correlation metric, along with Kernel Principal Component Analysis (KPCA) and autoencoders, is used to group and fuse health indicators (HIs), thereby obtaining a health indicator (HI) that effectively reflects the bearing degradation process. …”
Get full text

The Effect of Enriching Tea Infusion with Fruit Additives on Their Antioxidant Properties and the Profile of Bioactive Compounds by Barbara Chilczuk, Małgorzata Materska, Monika Staszowska-Karkut, Marzena Pabich

“…The LC-QTOF-MS method facilitated the identification of catechins and the determination of their content. The principal component analysis was used to define the relationship between catechins and the health-promoting properties of the beverages. …”
Get full text

Calibration of miniature air quality detector monitoring data with PCA–RVM–NAR combination model by Bing Liu, Yirui Zhang

“…First, correlation analysis is used to find out the main factors affecting pollutant concentrations. Second, principal component analysis is used to reduce the dimensionality of these main factors and extract their main information. …”
Get full text

Characterization of heavy metal contamination in groundwater of typical mining area in Hunan Province by Wenjie Hao, Huan Liu, Shuli Hao, Kuanzhen Mao

“…The statistical study results show that Mn, Se, As, and Sb are closely related to human mining activities and are polluted to varying degrees; the principal component analysis model indicates that the upstream monitoring points 26#, 22#, and 25# in the mining area groundwater are less polluted. …”
Get full text

Fault Diagnosis for Rolling Bearing under Variable Conditions Based on Image Recognition by Bo Zhou, Yujie Cheng

“…Third, due to the redundancy of the high-dimensional feature, kernel principal component analysis is utilized to reduce the feature dimensionality. …”
Get full text

Factors influencing the sustainability of university-incubated agribusinesses: the role of stigma failure, personality and motivation in Kenya by Racheal Gladys Nakiganda, Dickson Otieno Okello, Hillary Kiplangat Bett

“…The data were analysed through Principal Component Analysis (PCA) to identify key motivational dimensions. …”
Get full text

Analysis of Correlation Between Diatoms in Surface Sediments and Water Quality of Reservoirs in Source Region of Le'anhe River by HU Qiannan, JI Yong, YAN Ruyu, ZHANG Yue, WANG Yipeng, JIN Yi, BAI Dongchen

“…To explore the trophic level and the response of diatoms in surface sediments of reservoirs in the source region of Le'anhe River to the water environment,this paper conducts research on Duanxin Reservoir,Zhanggongshan Reservoir,Zhonglyu Reservoir,Datangwu Reservoir,and Shijing Reservoir in the source region of Le'anhe River.By the trophic level index (TLI),principal component analysis,and redundancy analysis (RDA),the water quality environment and the diatoms in surface sediments are taken as the research object and the research carrier,respectively,and the trophic state of reservoirs and the relationship between diatoms in surface sediments and water quality are qualitatively analyzed.The research results reveal that ① the water quality of Duanxin Reservoir belongs to Class I,i.e.…”
Get full text

Multivariate Statistics and Supervised Learning for Predictive Detection of Unintentional Islanding in Grid-Tied Solar PV Systems by Shashank Vyas, Rajesh Kumar, Rajesh Kavasseri

“…The resulting voltage and current data underwent dimensionality reduction using principal component analysis (PCA) which formed the basis for the application of Q statistic control charts for detecting the anomalous currents that could island the system. …”
Get full text

LPR-MLP: A Novel Health Prediction Model for Transmission Lines in Grid Sensor Networks by Yunliang Chen, Shaoqian Chen, Nian Zhang, Hao Liu, Honglei Jing, Geyong Min

“…The LPR-MLP model consists of two parts: (1) local binary pattern (LBP), principal component analysis (PCA), and ReliefF are used to process image data and meteorological and mechanical data and (2) the multilayer perceptron (MLP) method is then applied to build the prediction model. …”
Get full text

Authenticity Detection of Black Rice by Near-Infrared Spectroscopy and Support Vector Data Description by Hui Chen, Chao Tan, Zan Lin

“…The feasibility to utilize near-infrared (NIR) spectroscopy and support vector data description (SVDD) for such a goal is explored. Principal component analysis (PCA) is used for exploratory analysis and feature extraction. …”
Get full text

Effects of nitrogen, phosphorus and potassium formula fertilization on the yield and berry quality of blueberry. by Xinyu Zhang, Shuangshuang Li, Xiaoli An, Zejun Song, Yunzheng Zhu, Yi Tan, Xiaolan Guo, Delu Wang

“…Based on the comprehensive evaluation of principal component analysis and multi factor analysis of variance, the best fertilization combination for high-yield and good-quality blueberries was N1P2K2 (F2), that is, the best fertilization effect was that including N 100 g/plant, P2O5 25 g/plant, K2O 25 g/plant, applied in the form of ammonium sulfate (472 g/plant), superphosphate (41 g/plant) and potassium sulfate (40 g/plant), respectively.…”
Get full text

Nitrogen and Metal Ions Accumulation in Two Sensitive Himalayan Lichens From Western Nepal: A Reference for Ecosystem Health Monitoring by Suman Prakash Pradhan, Hirendra Bista, Bishal Lamsal, Nirvik Dotel, Bishnu Prasad Pandey, Subodh Sharma

“…Regression analysis revealed the least or no impacts of N and metal ions in physicochemical responses. The principal component analysis suggests the contribution of different environmental variable and their correlation with lichen’s variables. …”
Get full text

Evaluation of Genotype Diversity in Oat Germplasm and Definition of Ideotypes Adapted to the Mediterranean Environment by Anna Iannucci, Pasquale Codianni, Luigi Cattivelli

“…Accessions were very different for these evaluated traits, with wide variabilities found particularly for seed yield and fructo-oligosaccharide concentration (CV = 37%). Principal component analysis showed that the first six axes accounted for 81% of the variability. …”
Get full text

Spatial Patterns and Temporal Variability of Drought in Beijing-Tianjin-Hebei Metropolitan Areas in China by Wanyuan Cai, Yuhu Zhang, Qiuhua Chen, Yunjun Yao

“…Agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) were used to identify three different drought subregions R1, R2, and R3 based on the monthly precipitation values in BTHMA, which is located in southeast, north, and south of BTHMA, respectively. …”
Get full text

Multivariate Analysis of Confined Groundwater Hydrochemistry of a Long-Exploited Sedimentary Basin in Northwest China by Xuedi Zhang, Hui Qian, Hao Wu, Jie Chen, Liang Qiao

“…Accordingly, the characteristics of confined water were analyzed and collected from 33 sampling wells in spring of 2011, to determine the factors that influenced the composition and evolution of confined water, using principal component analysis (PCA), correlation analysis, groundwater evolution, and mineral dissolution/precipitation analysis. …”
Get full text

Prediction correction modeling of water-conducting fracture zones height due to repeated mining in close distance coal seams by Zhuoran Kang, Daming Yang, Pengfei Shen

“…This study compiles extensive measured data from various mining areas in China to analyze the coupling relationship between the WCFZ development height and six influencing factors: mining thickness, mining depth, coal seam spacing, hard rock lithology ratio, and the slope length of working face. Using principal component analysis and fuzzy comprehensive evaluation, we derived the combined weights of these factors. …”
Get full text

Integrating HRM with organizational strategy in Ethiopia: a study of manufacturing companies in Addis Ababa and adjacent zones of Oromia by Tekalign Gidi Kure, Meheret Ayenew Warota

“…We employed a mixed research approach and pragmatism research philosophy, gathering data through a structured questionnaire distributed to 371 respondents and conducting 24 key informant interviews with HR managers from the manufacturing sector. Using Principal Component Analysis (PCA), we have decomposed Strategic HRM into two dimensions: strategic orientation and strategic development. …”
Get full text

Genetic Diversity of Sangihe Nutmeg (Myristica fragrans Houtt.) Based on Morphological and ISSR Markers by Tanti Agustina, Abdul Razaq Chasani, Budi Setiadi Daryono, Muhammad Said Rifqi

“…In total, 31 morphological characteristics were examined, and molecular data of ISSR markers using five primers were analysed based on numerical taxonomy using the unweighted pair group method with arithmetic mean (UPGMA) and principal component analysis (PCA) methods. Results showed five major groups of Sangihe nutmeg based on seed variation, that is, thick round, thin round, thick oval, thin oval, and twin seeds, whereas the presence of variation in molecular characters was indicated by DNA polymorphisms between 0% and 33.33%. …”
Get full text

Effect of Lecithin and Mono- and Di-Glyceride on Quality and Shelf Life of Hazelnut Butter: Chemometric Approach by Amir Pourfarzad, Rezvaneh Shokouhi Kisomi

“…The peroxide values showed no significant changes during the 90-day storage. The principal component analysis (PCA) allowed discriminating among the features. …”
Get full text

Presentation and analysis of the Geotechnical Coastal Vulnerability Index and validation of its application to coastal erosion problems by Vasileios Boumpoulis, Nikolaos Depountis, Athanassios Dimas, George Papatheodorou

“…Furthermore, Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA) were applied in the methodology to assign weight factors to each variable. …”
Get full text