• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.707-714
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• 2024

Different degrees of natural radioactivity found in quartz can have negative consequences on health. Quartz vein along the investigated Abu Ramad area, Egypt, had its natural radioactivity assessed. The HPGe spectrometer was used to determine the role played by the radionuclides ²³⁸U, ²³²Th, and ⁴⁰K in the gamma radiation that was emitted, and the results showed that these concentrations are 484.64 ± 288.4, 36.8 ± 13.1 and 772.2 ± 134.6 Bq kg^-1 were higher than the corresponding reported global limits of 33, 45, and 412 Bq kg^-1 for each radionuclide (²³⁸U, ²³²Th, and ⁴⁰K). Among the radiological hazard parameters, the excess lifetime cancer risk (ELCR) is estimated and it's mean value of ELCR (1.2) is higher than the permissible limit of 0.00029. The relationship between the radionuclides and the associated radiological hazard characteristics was investigated based on multivariate statistical methods including Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA). According to statistical research, the radioactive risk of quartz is primarily caused by the ²³⁸U, ²³²Thand ⁴⁰K. Finally, applying quartz to building materials would pose a significant risk to the public.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• Journal of Environmental Science International
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• v.12 no.6
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• pp.665-676
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• 2003

To investigate the chemical characteristics of PM$\_$2.5/ in Seoul, Korea, atmospheric particulate matters were collected using a PM$\_$10/ dichotomous sampler including PM$\_$10/ and PM$\_$2.5/ inlet during the period of October 2000 to September 2001. The Inductively Coupled Plasma-Mass Spectromety (ICP-MS), ion Chromatography (IC) methods were used to determine the concentration of both metal and ionic species. A statistical analysis was performed for the heavy metals data set using a principal component analysis (PCA) to derived important factors inherent in the interactions among the variables. The mean concentrations of ambient PM$\_$2.5/ and PM/sub10/ were 24.47 and 45.27 $\mu\textrm{g}$/㎥, respectively. PM$\_$2.5/ masses also showed temporal variations both yearly and seasonally. The ratios of PM$\_$2.5/PM$\_$10/ was 0.54, which similar to the value of 0.60 in North America. Soil-related chemical components (such as Al, Ca, Fe, Si, and Mn) were abundant in PM$\_$10/, while anthropogenic components (such as As, Cd, Cr, V, Zn and Pb) were abundant in PM2s. Total water soluble ions constituted 30∼50 % of PM$\_$2.5/ mass, and sulfate, nitrate and ammonium were main components in water soluble ions. Reactive farms of NH$_4$$\^$+/were considered as NH$_4$NO$_3$ and (NH$_4$)$_2$SO$_4$ during the sampling periods. In the results of PCA for PM$\_$2.5/, we identified three principal components. Major contribution to PM$\_$2.5/ seemed to be soil, oil combustion, unidentified source. Further study, the detailed interpretation of these data will need efforts in order to identify emission sources.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.10
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• pp.1618-1628
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• 2013

Relationships between fatty acids and tocopherols in conventional and genetically modified peanut cultivars were studied by gas chromatography with flame ion detector and high performance liquid chromatography with fluorescence detection. Eight fatty acids and four tocopherol isomers in the sample set were identified and quantified. Oleic acid and linoleic acid are major fatty acids and the ratio of oleic and linoleic acids ranged from 1.11 to 16.26. Tocopherols contents were 6.76 to 12.24 for ${\alpha}$-tocopherol (T), 0.08 to 0.39 for ${\beta}$-T, 5.28 to 15.02 for ${\gamma}$-T, and 0.17 to 1.17 mg/100 g for ${\delta}$-T. Correlation coefficient (r) for fatty acids and tocopherols indicated a strong inverse relationship between oleic & linoleic acids (r=-0.97, P<0.05) and positive relationships between palmitic & linoleic acids (r=0.95, P<0.05) and ${\gamma}$-T & ${\delta}$-T (r=0.83, P<0.05). Principal component analysis (PCA) of fatty acids and tocopherols gave four significant principal components (PCs, with eigenvalues>1), which together account for 85.49% of the total variance in the data set with PC1 and PC2 contributing 45.27% and 21.33% of the total variability, respectively. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed by palmitic, oleic, linoleic, and gondoic acids, while PC2 was by behenic acid, ${\beta}$-T, and ${\gamma}$-T. The score plot generated by PC1-PC2 identified sample clusters in the two spatial planes based on the oleic and linoleic acids. The score plot PC3-PC4 didn't separate sample groups.

• Korean Journal of Plant Resources
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• v.20 no.4
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• pp.298-303
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• 2007

To examine taxonomic relationships among 24 leaf mustard allies (Brassica juncea) derived from domestic collections and introduced species, principal component analysis (PCA) and cluster analysis on 16 morphological characters were carried out. Of 16 characters, total fresh weight, total dry weight, shoot fresh weight and leaf length were useful characters for the understanding of taxonomic relationships among them. Cluster analysis using scores of the principal components indicated that 24 leaf mustards could be grouped into domestic collections and introduced species at 1.0 of average distance in UPGMA. Moreover, in experiment of $F_{1}$ recombination test, heterosis appeared greatly in Sanchiohbachirimen takana A ${\times}$ Akaohba takana, Goheung namyang ${\times}$ Sanchiohbachirimen takana B, and Goheung namyang ${\times}$ Akaohba takana cross combinations. Sanchiohbachirimen takana A and Akaohba takana have a high parent combining ability for breeding cultivars using cytoplasmic male sterility.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.38-38
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• 2023

Sorghum (Sorghum bicolor L.) is a promising biomass crop with a high lignocellulose content. This study aimed to select high salt-tolerance sorghum lines for cultivation on reclaimed land. Using 7-day seedlings of the sorghum population consisted of 71 radiation-derived mutants (M₂ to M₆) and 33 genetic resources, survival rate (SR), plant height (PH), root length (RL), fresh weight (FW), and chlorophyll content (CC) were measured for two weeks after 102 mM (0.6%) NaCl treatment. Furthermore, the characteristics of the sorghum population were confirmed using correlation analysis, PCA (principal component analysis), and the FCE (fuzzy comprehensive evaluation) method. Under 102 mM NaCl conditions, SR ranged from 4.9 (IS645-200-6) to 82.4% (KLSo79125-200-1), with an average of 49.9%. PH varied from 7.5 (Mesusu-100-2) to 33.2 cm (DINE-A-MITE-100-2-10), with an average of 20.4 cm. RL ranged from 1.0 (IS645-200-1) to 17.0 cm (30-100-2), with an average of 7.7 cm. FW varied from 0.1 (IS645-200-6) to 4.5 g/plant (DINE-A-MITE-100-2-10), with an average of 2.1 g/plant. CC ranged from 0.9 (DINE-A-MITE-100-2-2) to 3.1 mg/g (IS12937), with an average of 1.7 mg/g. An overall positive correlation, with SR and FW (r = 0.86, P < 0.01), and FW and CC (r = 0.79, P < 0.01), was shown by correlation analysis. Among the five traits, two principal components were extracted by PCA analysis. PC1 was significantly associated with FW, while PC2 was highly involved with RL. To evaluate the salt tolerance level of the sorghum population when an FCE based on trait data was performed, MFV (membership function value) was 0.68. As a result of compiling the MFV of each line, eight lines with MFV > 0.68 were selected. Ultimately, the radiation-derived mutant lines, DINE-A-MITE-100-2-10 and DINE-A-MITE-100-2-12 were selected as salt-tolerant sorghum lines. The results are expected to inform salt-tolerant sorghum breeding programs, and the high salt-tolerance sorghum lines might be advantageous for cultivation on reclaimed land.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.757-762
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• 2010

Since the quality and performance of medicinal products are heavily dependent upon the size, shape and polymorphism of active pharmaceutical ingredients(APIs), their crystallization has been regarded as one of the most important pharmaceutical processes. In this study, NIR-based inline measurements were employed to monitor key attributes of API particles real-time during the crystallization process. Principal component analysis(PCA) method was selected to correlate inline NIR spectra while the well-known aspirin was studied as a model drug. According to our characterization results, the ratio of ethanol to acetone did not cause any change in polymorphism, but resulted in a significant difference in the nucleation time, crystal growth and crystal shape. These phenomenological changes were well correlated with the PCA's implications. It turned out that the NIR-based inline monitoring technology can be employed well in observing and predicting key quality attributes such as crystal size during pharmaceutical crystallization processes.

• Journal of KIISE
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• v.42 no.12
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• pp.1535-1543
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• 2015

The brain-computer interface obtains a user's electroencephalogram as a replacement communication unit for the disabled such that the user is able to control machines by simply thinking instead of using hands or feet. In this paper, we propose a feature extraction method based on a non-selected filter by SBCSP to classify motor imagery EEG. First, we divide frequencies (4~40 Hz) into 4-Hz units and apply CSP to each Unit. Second, we obtain the FLD score vector by combining FLD results. Finally, the FLD score vector is projected onto the optimal plane for classification using PCA. We use BCI Competition III dataset IVa, and Extracted features are used as input for LS-SVM. The classification accuracy of the proposed method was evaluated using $10{\times}10$ fold cross-validation. For subjects 'aa', 'al', 'av', 'aw', and 'ay', results were $85.29{\pm}0.93%$, $95.43{\pm}0.57%$, $72.57{\pm}2.37%$, $91.82{\pm}1.38%$, and $93.50{\pm}0.69%$, respectively.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.657-672
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• 2008

The purposes of this study are to investigate the hydrogeochemical characteristics of groundwaters around Keumsan municipal landfill, and to evaluate the contaminant dispersion from the landfill and its environmental impact. To achieve these goals, groundwater quality logging, hydrochemical analysis, multivariate statistical analysis, and contaminant transport modeling were performed. The water quality logging indicated a leaking from the landfill at the depth of 4-12m around a leachate sump. Electrical conductivity data indicated that groundwaters within 70-100m from landfill were affected by the landfill leakage. Principal components 1 and 2 obtained from principal components analysis (PCA) reflect the influence of leachate and the characteristics of aquifer media, respectively. The results of principal component analysis also indicated the natural attenuation processes such as cation exchange, sorption, and microbial biodegradation. The modeling results showed that groundwater flow westward along a valley from the landfill and contaminants transport accordingly.