• Journal of Multimedia Information System
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• v.4 no.4
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• pp.189-194
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• 2017

In this study, we propose a method which is based on "Image segmentation by histogram thresholding using hierarchical cluster analysis"/HCA/ and "A nonparametric approach for histogram segmentation"/NHS/. HCA method uses that all histogram bins are one cluster then it reduces cluster numbers by using distance metric. Because this method has too many clusters, it is more computation. In order to eliminate disadvantages of "HCA" method, we used "NHS" method. NHS method finds all local minima of histogram. To reduce cluster number, we use NHS method which is fast. In our approach, we combine those two methods to eliminate disadvantages of Arifin method. The proposed method is not only less computational than "HCA" method because combined method has few clusters but also it uses local minima of histogram which is computed by "NHS".

• Journal of the Korean Society of Food Culture
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• v.31 no.1
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• pp.105-110
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• 2016

The objective of this study was to determine sensory profiles of rice confections. The samples used in this study obtained from Korea (traditional Korea rice snack and local specialty rice snack) and three countries (USA, Japan, and China) were evaluated and compared. The sensory characteristics of five kinds of rice confections were evaluated using a sensory test and were analyzed via quantitative description analysis (QDA), principal component analysis (PCA), and hierarchical cluster analysis (HCA). In the descriptive analysis, 10 trained panelists evaluated sensory characteristics consisting of 19 attributes, and there were significant differences (p<0.05) among the 16 characteristics. For the descriptive data, multivariate analysis of variance was carried out and identified differences among the samples. The PCA of rice confections for the first two principal components could explain 85.66% of the variations. The Korean, Japanese, and Chinese rice confections were savory, gritty, and particle-sized, the other Korean local specialty rice confections were fruity, sweet, honey-flavored, compact, and crispy, and those from the USA were glossy, grainy, bright, adhesive, cohesive, crispy, and sweet.

• Environmental Engineering Research
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• v.24 no.2
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• pp.279-288
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• 2019

To obtain insightful knowledge of geochemical process controlling fluoride enrichment in groundwater of the villages near Shilabati river bank, West Bengal, India, multivariate statistical techniques were applied to a subgroup of the dataset generated from major ion analysis of groundwater samples. Water quality analysis of major ion chemistry revealed elevated levels of fluoride concentration in groundwater. Factor analysis (FA) of fifteen hydrochemical parameters demonstrated that fluoride occurrence was due to the weathering and dissolution of fluoride-bearing minerals in the aquifer. A strong positive loading (> 0.75) of fluoride with pH and bicarbonate for FA indicates an alkaline dominated environment responsible for leaching of fluoride from the source material. Mineralogical analysis of soli sediment exhibits the presence of fluoride-bearing minerals in underground geology. Hierarchical cluster analysis (HCA) was carried out to isolate the sampling sites according to groundwater quality. With HCA the sampling sites were isolated into three clusters. The occurrence of abundant fluoride in the higher elevated area of the observed three different clusters revealed that there was more contact opportunity of recharging water with the minerals present in the aquifer during infiltration through the vadose zone.

• Bulletin of the Korean Chemical Society
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• v.30 no.10
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• pp.2287-2293
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• 2009

Gas Chromatography-Mass Spectrometry (GC-MS) fingerprint analysis, Principle Components Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were introduced for quality assessment of Curcuma longa L. (C. longa). The GC-MS fingerprint method was developed and validated by analyzing 33 batches of samples of C. longa from different geographic locations. 18 chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression. Two principal components (PCs) were extracted by PCA. C. longa collected from Guizhou and Fujian were separated from other samples by PC1, capturing 71.83% of variance. While, PC2 contributed for their further separation, capturing 11.13% of variance. HCA confirmed the result of PCA analysis. Therefore, GC-MS fingerprint study with chemometric techniques provides a very flexible and reliable method for quality assessment of C. longa.

• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1547-1553
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• 2011

An effective analytical method of gas chromatography/mass spectrometry (GC/MS) was developed for the rapid determination of essential oils in the crude extract of Acorus species (Acorus gramineus, Acorus tatarinowii, and Acorus calamus). Major phenypropanoids (${\beta}$,${\alpha}$-asarone isomers, euasarone, and methyleugenol) and ${\beta}$-caryophyllene in Acorus species were used as marker compounds and determined for the quality control of herbal medicines. To extract marker compounds, various extraction techniques such as solvent immersion, mechanical shaking, and sonication were compared, and the greatest efficiency was observed with sonication extraction using petroleum ether. The dynamic range of the GC/MS method depended on the specific analyte; acceptable quantification was obtained between 10 and 2000 ${\mu}g/mL$ for ${\beta}$-asarone, 10 and 500 ${\mu}g/mL$ for ${\alpha}$-asarone, 10 and 200 ${\mu}g/mL$ for methyleugenol, and between 5 and 100 ${\mu}g/mL$ for ${\beta}$-caryophyllene. The method was deemed satisfactory by inter- and intra-day validation and exhibited both high accuracy and precision, with a relative standard deviation < 10%. Overall limits of detection were approximately 0.34-0.83 ${\mu}g/mL$, with a standard deviation (${\sigma}$)-to-calibration slope (s) ratio (${\sigma}$/s) of 3. The limit of quantitation in our experiments was approximately 1.13-3.20 ${\mu}g/mL$ at a ${\sigma}$/s of 10. On the basement of method validation, 20 samples of Acorus species collected from markets in Korea were monitored for the quality control. In addition, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed on the analytical data of 20 different Acorus species samples in order to classify samples that were collected from different regions.

• Journal of Applied Biological Chemistry
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• v.64 no.2
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• pp.127-131
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• 2021

Perilla frutescens var. crispa (Pfc), a herb belonging to the mint family (Lamiaceae), has been used for medicinal and aromatic purposes. In the present study, we analyzed the variation in the chemical composition of essential oils (EOs) obtained from five different genotypes of Pfc collected from different regions. Based on principal component analysis (PCA) and hierarchical cluster analysis (HCA), we identified three groups: PA type containing perillaldehyde, PP type containing dillapiole, and 2-acetylfuran type. To assess the correlation between EO components and antimicrobial activities, we compared classification results generated by PCA and HCA based on antimicrobial activity values. The findings suggested that the major compounds obtained from EOs of Pfc are responsible for their antimicrobial activities. Chemotypes of Pfc plants are essentially qualitative traits that are important for breeders. The present findings provide potential information for breeding Pfc as an antimicrobial agent.

• Preventive Nutrition and Food Science
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• v.18 no.3
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• pp.214-217
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• 2013

Twenty-nine Korean wheat cultivars were analyzed for 8 important minerals (Cu, Fe, Mn, Zn, Ca, K, Mg and P) using Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). A hierarchical cluster analysis (HCA) was applied to classify wheat cultivars, which has a similarity in mineral compositions. The concentration ranges of the micro-minerals Cu, Fe, Mn, and Zn: 0.12~0.71 mg/100 g, 2.89~5.89 mg/100 g, 1.65~4.48 mg/100 g, and 2.58~6.68 mg/100 g, respectively. The content ranges of the macro-minerals Ca, K, Mg and P: 31.3~46.3 mg/100 g, 288.2~383.3 mg/100 g, 113.6~168.6 mg/100 g, and 286.2~416.5 mg/100 g, respectively. The HCA grouped 6 clusters from all wheat samples and a significant variance was observed in the mineral composition of each group. Among the 6 clusters, the second group was high in Fe and Ca, whereas the fourth group had high Cu, Mn and K concentrations; the fifth cluster was high in Zn, Mg and P. The variation in mineral compositions in Korean wheat cultivars can be used in the wheat breeding program to develop a new wheat cultivar with high mineral content, thus to improve the nutritional profile of wheat grains.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.407-414
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• 2013

This study was conducted to classify forest cover types using the multivariate statistical analysis in the natural forest of western Mt. Jiri. On the basis of the vegetation data by point quarter sampling, the adopted analytical methods were species-area curve (SAC), hierarchical cluster analysis (HCA), indicator species analysis (ISA), and multiple discriminant analysis (MDA). SAC selected the outlier tree species which was likely to have no influence on the classification of forest cover types, excluded from all analytical process. Based on forest vegetative information, HCA classified the study area into 2 to 10 clusters and ISA indicated that the optimal number of clusters were seven. MDA was taken to test the clusters that classified with HCA and ISA. The seven clusters were classified appropriately as overall classification success were 91.3%. The classified forest cover types were named by the ratio of the dominant species in the upper layer of each cluster. They were (1) Quercus mongolica Pure forest, (2) Mixed mesophytic forest, (3) Q. mongolica - Q. serrata forest, (4) Abies koreana - Q. mongolica forest, (5) Fraxinus mandshurica forest, (6) Q. serrata forest, and (7) Carpinus laxiflora forest.

• Environmental Engineering Research
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• v.22 no.1
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• pp.31-39
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• 2017

The primary purpose of this research is to understand those elements that define heavy metals contamination and to propose a novel assessment method based on principal component analysis (PCA) in the Yangping River region of Lingbao City, China. This paper makes detailed calculations regarding such factors the single-factor assessment ($P_i$) and Nemerow's multi-factor index ($P_N$) of heavy metals found in the surface water of the Yangping River. The maximum values of $P_i$ (Cd) and $P_i$ (Pb) were determined to be 892.000 and 113.800 respectively. The maximum value of $P_N$ was calculated to be 639.836. The results of Pearson's correlation analysis, hierarchical cluster analysis, and PCA indicated heavy metal groupings as follows: Cu, Pb, Zn and As, Hg, Cd. The PCA-based pollution index ($P_{an}$) of samplings was subsequently calculated. The relative coefficient square was valued at 0.996 between $P_{an}$ and $P_N$, which indicated that $P_{an}$ is able to serve as a new heavy metal pollution index; not only this index able to eliminate the influence of the maximum value of $P_i$, but further, this index contains the principal component elements needed to evaluate heavy metal pollution levels.

• Journal of Korea Water Resources Association
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• v.42 no.2
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• pp.149-160
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• 2009

The objective of this study is to suggest parameter regionalization scheme which is integrated two multivariate statistical methods: principal components analysis(PCA) and hierarchical cluster analysis(HCA). This technique is to apply semi-distributed rainfall-runoff model on ungauged catchments. 7 catchment characteristics (area, mean altitude, mean slope, ratio of forest, water content at saturation, field capacity and wilting point) are estimated for 109 mid-sized sub-basins. The first two components from PCA results account for 82.11% of the total variance in the dataset. Component 1 is related to the location of the catchments relevant to the altitude and Component 2 is connected with the area of these. 103 ungauged catchments are clustered using HCA as the following 6 groups: Goesan 23, Andong 6, Imha 5, Hapcheon 21, Yongdam 4, Seomjin 44. SWAT model is used to simulate runoff and the parameters of the model on the 6 gauged basins are estimated. The model parameters were regionalized for Soyang, Chungju and Daecheong dam basins which are assumed as ungauged ones. The model efficiency coefficients of the simulated inflows for these three dams were at least 0.8. These results also mean that goodness of fit is high to the observed inflows. This research will contribute to estimate and analyze hydrologic components on the ungauged catchments.