• Journal of the Korean earth science society
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• v.35 no.4
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• pp.225-236
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• 2014

Multivariate statistical analyses have been extensively applied to hydrochemical measurements to analyze and interpret the data. This study examines anthropogenic factors obtained from applications of correspondence analysis (CA) and principal component analysis (PCA) to a hydrogeochemical data set. The goal was to synthesize the hydrogeochemical information using these multivariate statistical techniques by incorporating hydrogeochemical speciation results calculated by the program, commonly used, WATEQ4F included in the NETPATH. The selected case study was LPG underground storage caverns, which is located in the southeastern Korea. The highly alkaline groundwaters at this study area are an analogue for the repository system. High pH, speciation of Al and possible precipitation of calcite characterize these groundwaters. Available groundwater quality monitoring data were used to confirm these statistical models. The present study focused on understanding the hydrogeochemical attributes and establishing the changes of phase when two anthropogenic effects (i.e., disinfection activity and cement pore water) in the study area have been introduced. Comparisons made between two statistical results presented and the findings of previous investigations highlight the descriptive capabilities of PCA using calculated saturation index and CA as exploratory tools in hydrogeochemical research.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.3
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• pp.137-144
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• 2015

The purpose of this study is to develop an warning system to detect real-time water quality abnormality using a multivariate statistical approach. In this study, we applied principal component analysis among multivariate data analyses which was used for the correlation between water quality parameters considering the real-time algorithm to determine abnormality in water quality. We applied our approach to real field data and showed the utilization of algorithm for the real-time monitoring to find water quality abnormality. In addition, our approach with Korea Meterological Adminstration database identified heavy rain data due to climate change is one of the most important factors to explain water quality abnormality.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.719-725
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• 2011

To apply TMAH-based Py-MS to a field biological detection system for real-time classification of cell-type, reproducible patterns of the TMAH-based Py-MS spectra was known as a critical factor for classification but was seriously disturbed by quantity of cells injected into pyro-tube. This factor is an exterior variable that could not be complemented by improving the performance of the TMAH-based Py-MS instrument. One of idea to solve the knotty problem has been flashed from "Top-down proteomics for identification of intact microoganisms". That is, biomarker peaks are selected from complicate Py-MS spectra for intact microoganisms by tracing out their origins, based on Py-MS spectra for the featured components of different cell-types, in Top-down approach. This idea has been tested in classification of different Gram-type microoganisms. Through the analyses of spectra for the featured components - peptidoglycan and lipoteichoic acid for Gram-positive cells and lipopolysaccharide and lipid A for Gram-negative cells - with comparing to the spectra the corresponding Gram-type cells in the Top-down approach, biomarker peaks were selected to carry out PCA(Principal Component Analysis) in order to see classification of different Gram-types, resulting in significant improvement of their classification. Furthermore, weighting biomarker peaks on intact cell's spectra, based on the data for the featured components of the Gram-types, contributed to elevate classification performance.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.163-171
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• 2016

We investigated the intensity and pattern of the scent produced by diploid and tetraploid Cymbidium flowers, using an electronic nose with 6 metal oxide sensors (MOS). The MOS responses were evaluated by principal component analysis, discriminant function analysis, and sensor data. These analyses revealed that tetraploid flowers had a stronger scent than diploid flowers in Cymbidium Golden Elf 'Sundust'. Furthermore, among the different flower parts-column, lip, and petals-the column produced the strongest scent. There was no significant difference between the flowering periods of diploid and tetraploid potted Cymbidium Golden Elf 'Sundust' and Cymbidium Elma 'Orient Toyo' grown in a greenhouse. Moreover, there were no significant differences between the number of flowers per flower stem and the length of flower stems on the diploid and tetraploid plants of these two Cymbidium cultivars. This study provides potentially useful information for the breeding of polyploidy Cymbidium in the floriculture industry.

• Korean Journal of Breeding Science
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• v.40 no.4
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• pp.361-370
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• 2008

In order to better understand the morphological differentiation of the two cultivated types of Perilla crop and their weedy types in Korea and Japan, we studied the variation of 62 accessions by examining 15 morphological characteristics. By using ANOVA (one-way analysis of variance), we determined that var. frutescens and var. crispa showed significant morphological differences in terms of plant height and seed weight. Furthermore, cultivated var. frutescens and var. crispa could also be clearly discriminated from one another using PCA (principal component analysis). Specifically, quantitative and qualitative characteristics such as plant height, seed weight, degree of pubescence, shape of leaf, color of leaf, fragrance of plant, color of flower, color of stem and seed size greatly contributed to differences seen in the positive and negative direction on the first axis. In our study, most accessions of cultivated var. frutescens and those of its weedy type could be clearly discriminated from one another, however, most accessions of cultivated and weedy types of var. crispa were not clearly discriminated by the ANOVA and PCA analyses. These results indicated that cultivated var. frutescens can be considered to be a domesticated form, while the cultivated var. crispa can not be considered to be a domesticated form in Korea and Japan. It is our belief that our results concerning the morphological variations among cultivated types of Perilla crop and their weedy types in Korea and Japan will help ensure the long-term success of breeding programs and maximize the use of the germplasm resources in Korea.

• Environmental Engineering Research
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• v.24 no.1
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• pp.45-53
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• 2019

Water and soil properties in paddy fields subjected to organic and conventional farming were characterized over the rice cycle in South Korea. To achieve the goals of this study, we sampled and analyzed soil and water from 24 organic paddy plots and 11 conventional paddy plots in March, May, August, and October 2016. The results were analyzed using statistical analyses, including analysis of variance (ANOVA), cluster analysis, and principal component analysis. The ANOVA results showed that water content (WC), electrical conductivity (EC), organic matter (OM), and available phosphorus ($P_2O_5$) in soil varied significantly (p < 0.01) depending on the farming method. Higher OM, EC, and $P_2O_5$ of soil were observed in the conventional paddies than in the organic paddies. All soil properties, except pH and ammonium, depended on seasonal variation. Cluster analysis revealed that soil properties in May were distinctly separated from those in other seasons mainly due to basal fertilization. The principal component analysis distinguished the soil properties in different seasons, but such a distinction was not observed between the soil properties in organic and conventional paddies. Low contents of WC, OM, and total N were observed in March. High concentrations of nitrate and total P were observed in May, but these were low in August and October. The soils from October were also characterized by high concentrations of EC and $P_2O_5$. These results indicate that the sampling time for soil and water can significantly influence the evaluation of soil properties with different farming methods.

• Ocean and Polar Research
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• v.44 no.1
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• pp.13-27
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• 2022

The Yeongsan River estuary was altered by a sea dike built in 1981 and the sluice gates in the dike were extended recently in 2014. The construction has caused changes in water properties and hydrodynamics and also produced disturbances including hypoxia and algal blooms. We analyzed the water quality and chlorophyll-a data (2009-2018) collected seasonally at 3 stations (Sts. 1-3) along the channel of the estuary by the Marine Environmental Monitoring System. Variations in water quality and chlorophyll-a (an index of phytoplankton biomass) were examined and their stressors were also identified by statistics including correlation and multivariate principal component analyses (PCA). The water quality was mainly affected by freshwater discharge from the dike. Salinity, nutrients and chlorophyll-a were especially affected by the discharge and the effect enhanced during summer and at the upper region near the sea dike decreasing downstream. Three factors were extracted for each station in the PCA accounting for 66.07-72.42% of the variations. The first was an external factor associated with freshwater discharge and the second and third were seasonal or biological factors. The results indicate that the water quality is more affected by short-termed and episodic events such as freshwater discharge than seasonal events and the influence of freshwater discharge on water quality is more extensive than that previously reported. This suggests that the boundary of the estuary should be extended to take into account the findings of this study and a management strategy linked to the freshwater zone is required to manage the integrity and water quality of the Yeongsan River estuary.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.95-103
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• 2022

Quick and accurate understanding of the situation in a severe accident is essential for conducting the appropriate accident management and response using the accident diagnosis information. This study employed deep learning technology to diagnose severe accidents through the major safety parameters transferred from a nuclear power plant (NPP) to AtomCARE. After selecting the major accident scenarios to consider, a learning database was established for particular scenarios affiliated with major scenarios by performing a large number of severe accident analyses using MAAP5 code. The severe accident diagnosis technology, which classifies detailed accident scenarios using the major safety parameters from NPPs, was developed by training it with the established database . Verification and validation were conducted by blind test and principal component analysis. The technology developed in this study is expected to be extended and applied to all severe accident scenarios and be utilized as a base technology for quick and accurate severe accident diagnosis.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.123-138
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• 2022

Korea has been huge investments in its port system, annually upgrading its infrastructure to turn the ports into Asian hub port. However, while Busan port is ranked fifth globally for container throughput, Other Korean ports are ranked much lower. This article applies Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) to evaluate selected major Korean seaports' operational efficiency and productivity from 2010 to 2018. It further integrates Principal Component Analysis (PCA) into DEA, with the PCA-DEA combined model strengthening the basic DEA results, as the discriminatory power weakens when the variable number exceeds the number of Decision Making Units(DMU). Meanwhile, MPI is applied to measure the seaports' productivity over the years. The analyses generate efficiency and productivity rankings for Korean seaports. The results show that except for Gwangyang and Ulsan port, none of the selected seaports is currently efficient enough in their operations. The study also indicates that technological progress has led to impactful changes in the productivity of Korean seaports.