• 제목/요약/키워드: hierarchical cluster analysis (HCA)

검색결과 19건 처리시간 0.024초

Hierarchical Cluster Analysis Histogram Thresholding with Local Minima

  • Sengee, Nyamlkhagva;Radnaabazar, Chinzorig;Batsuuri, Suvdaa;Tsedendamba, Khurel-Ochir;Telue, Berekjan
    • Journal of Multimedia Information System
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    • 제4권4호
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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".

묘사분석을 이용한 쌀 과자의 관능적 특성 연구 (Sensory Characteristics of Rice Confections by Descriptive Analysis)

  • 정다은;양정은;정라나
    • 한국식생활문화학회지
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    • 제31권1호
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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.

Application of multivariate statistics towards the geochemical evaluation of fluoride enrichment in groundwater at Shilabati river bank, West Bengal, India

  • Ghosh, Arghya;Mondal, Sandip
    • Environmental Engineering Research
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    • 제24권2호
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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.

Quality Assessment of Curcuma longa L. by Gas Chromatography-Mass Spectrometry Fingerprint, Principle Components Analysis and Hierarchical Clustering Analysis

  • Li, Ming;Zhou, Xin;Zhao, Yang;Wang, Dao-Ping;Hu, Xiao-Na
    • Bulletin of the Korean Chemical Society
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    • 제30권10호
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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.

Development of Fingerprints for Quality Control of Acorus species by Gas Chromatography/Mass Spectrometry

  • Yu, Se-Mi;Kim, Eun-Kyung;Lee, Je-Hyun;Lee, Kang-Ro;Hong, Jong-Ki
    • Bulletin of the Korean Chemical Society
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    • 제32권5호
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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.

Variation in essential oil composition and antimicrobial activity among different genotypes of Perilla frutescens var. crispa

  • Ju, Hyun Ju;Bang, Jun-Hyoung;Chung, Jong-Wook;Hyun, Tae Kyung
    • Journal of Applied Biological Chemistry
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    • 제64권2호
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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.

Mineral Compositions of Korean Wheat Cultivars

  • Choi, Induck;Kang, Chon-Sik;Hyun, Jong-Nae;Lee, Choon-Ki;Park, Kwang-Geun
    • Preventive Nutrition and Food Science
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    • 제18권3호
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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.

다변량 통계 분석법의 연속 적용에 의한 서부 지리산 천연림의 산림 피복형 분류 (The Classification of Forest Cover Types by Consecutive Application of Multivariate Statistical Analysis in the Natural Forest of Western Mt. Jiri)

  • 정상훈;김지홍
    • 한국산림과학회지
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    • 제102권3호
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    • pp.407-414
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    • 2013
  • 본 연구는 다변량 통계 분석법을 이용하여 지리산 서부 천연림을 대상으로 산림 피복형을 분류하기 위해 실시하였다. 점표본법에 의한 식생자료를 바탕으로, 수종-표본점 곡선, 계층적 군집분석, 지표종분석, 다중판별분석 등의 다변량 통계 분석법을 이용하여 식생자료를 분석하였다. 수종-표본점 곡선에서는 산림 피복형 분류에서 전혀 영향력이 없는 수종들을 예외값으로 제거하였다. 예외값을 제외한 산림식생정보를 바탕으로 계층적 군집분석을 이용하여 연구대상지를 2~10개의 클러스터로 분류하였으며, 지표종분석을 통해 연구대상지의 적정 클러스터 수는 7개인 것으로 파악되었다. 이를 통계적으로 검증하기 위해 다중판별분석을 실시하였고, 91.3%가 정확하게 분류되어, 연구대상지 산림 피복형의 개수는 7개가 적당한 것으로 나타났다. 각 클러스터 상층의 우점수종 비율에 따라 신갈나무순림, 중생혼합림, 신갈나무-졸참나무림, 구상나무-신갈나무림, 들메나무림, 졸참나무림, 서어나무림으로 산림 피복형을 명명하였다.

Novel assessment method of heavy metal pollution in surface water: A case study of Yangping River in Lingbao City, China

  • Liu, Yingran;Yu, Hongming;Sun, Yu;Chen, Juan
    • Environmental Engineering Research
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    • 제22권1호
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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.

다변량 통계분석을 이용한 준분포형 유출모형 매개변수 지역화 (Parameter Regionalization of Semi-Distributed Runoff Model Using Multivariate Statistical Analysis)

  • 이병주;정일원;배덕효
    • 한국수자원학회논문집
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    • 제42권2호
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    • pp.149-160
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    • 2009
  • 본 연구에서는 미계측유역에 대한 준분포형 강우-유출모형을 적용하기 위한 방법으로 두 개의 다변량 통계기법인 주성분분석과 계층적 군집분석을 연계한 매개변수 지역화 기법을 제안하였다. 109개 중권역 유역에 대해 7개 유역특성인자(유역면적, 평균표고, 평균경사, 산림면적비, 포화토양수분량, 포장용수량, 영구위조점)를 추출하였으며 주성분분석을 수행한 결과 제1, 2 성분이 전체자료의 82.11%를 설명하는 것으로 나타났다. 제1성분은 유역위치, 제2성분은 유역규모와 관계가 있는 것으로 분석되었으며 이들 성분점수로부터 군집분석을 이용하여 103개 미계측유역을 6개 계측유역으로 분류한 결과 괴산댐 23개, 안동댐 6개, 임하댐 5개, 합천댐 21개, 용담댐 4개, 섬진강댐 44개의 미계측 유역을 포함하는 것으로 나타났다. 유출모형은 SWAT 모형을 선정하였으며 6개 계측유역에 대한 매개변수를 추정하였다. 매개변수 지역화 결과의 적용성을 평가하기 위해 미계측유역으로 가정한 소양, 충주, 대청댐 상류유역에 대해 지역화된 매개변수를 이용하여 유출해석을 수행한 결과 모형효율성계수가 0.8 이상으로 관측치와 적합도가 매우 높게 나타났다. 이상의 결과로부터 다변량 통계분석을 이용한 유출매개변수 지역화 방법은 미계측유역의 유출모의시활용 가능함을 확인하였다.