• The Plant Pathology Journal
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• 제34권5호
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• pp.381-392
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• 2018

Clavibacter michiganensis subsp. michiganesis (Cmm) is a quarantine-worthy pest in $M{\acute{e}}xico$. The implementation and validation of new technologies is necessary to reduce the time for bacterial detection in laboratory conditions and Raman spectroscopy is an ambitious technology that has all of the features needed to characterize and identify bacteria. Under controlled conditions a contagion process was induced with Cmm, the disease epidemiology was monitored. Micro-Raman spectroscopy ($532nm\;{\lambda}$ laser) technique was evaluated its performance at assisting on Cmm detection through its characteristic Raman spectrum fingerprint. Our experiment was conducted with tomato plants in a completely randomized block experimental design (13 plants ${\times}$ 4 rows). The Cmm infection was confirmed by 16S rDNA and plants showed symptoms from 48 to 72 h after inoculation, the evolution of the incidence and severity on plant population varied over time and it kept an aggregated spatial pattern. The contagion process reached 79% just 24 days after the epidemic was induced. Micro-Raman spectroscopy proved its speed, efficiency and usefulness as a non-destructive method for the preliminary detection of Cmm. Carotenoid specific bands with wavelengths at 1146 and $1510cm^{-1}$ were the distinguishable markers. Chemometric analyses showed the best performance by the implementation of PCA-LDA supervised classification algorithms applied over Raman spectrum data with 100% of performance in metrics of classifiers (sensitivity, specificity, accuracy, negative and positive predictive value) that allowed us to differentiate Cmm from other endophytic bacteria (Bacillus and Pantoea). The unsupervised KMeans algorithm showed good performance (100, 96, 98, 91 y 100%, respectively).

• Earthquakes and Structures
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• 제23권6호
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• pp.549-580
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• 2022

This paper assesses the influences of modeling assumptions and uncertainties on the performance of the non-linear finite element (FE) model updating procedure and model clustering method. The results of a shaking table test on a four-story steel moment-resisting frame are employed for both calibrations and clustering of the FE models. In the first part, simple to detailed non-linear FE models of the test frame is calibrated to minimize the difference between the various data features of the models and the structure. To investigate the effect of the specified data feature, four of which include the acceleration, displacement, hysteretic energy, and instantaneous features of responses, have been considered. In the last part of the work, a model-based clustering approach to group models of a four-story frame with similar behavior is introduced to detect abnormal ones. The approach is a composition of property derivation, outlier removal based on k-Nearest neighbors, and a K-means clustering approach using specified data features. The clustering results showed correlations among similar models. Moreover, it also helped to detect the best strategy for modeling different structural components.

• 한국의류학회지
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• 제22권2호
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• pp.203-214
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• 1998

The purpose of this study is to classify the upper body of women into several kinds of somatotypes, using the method of Surgical Tape and making their shells. The subjects are 53 females 30 to 39 years-old. Fifty-three anthropometric data are measured per shell of bodysurface; six somatotype factors are obtained through principal component analysis and orthogonal rotation by the method of Varimax, Somatotype of women's upper body is achieved by cluster analysis, using the standardized factor score as an independent variable and the FASTCLUS of SAS by Kmeans. The results are as follows: 1. The number of the factors which explain the somatotype is six and those factors comprise 76.12 percent of total variance. Factor 1: related to the size of shape in the front of upper body Factor S: related to the size of shape in the back of upper body Factor 3: related to the type of the upper chest over the chest circumference line Factor 4: related to the length of·the upper body Factor 5: related to the part of the neck Factor 6: related to the type of the lower chest under the chest circumference line 2. Cluster analysis results in classification of upper body into five clusters. Cluster L: the length is the largest and the circumference is small. The part of waist is the largest and widest among surface areas. Cluster 2: Slender body line from chest to waist is characteristic. The length is longer. The part of upper and lower chest is larger among surface areas. Cluster S: the circumference is the smallest and armhole is small. The length and surface area are small. Cluster 4: the circumference and armhole is the largest. The length is the smallest. Cluster 5: the circumference is average and the length is a little long. The body line(silhouette) from chest to waist is curved slightly.

• 한국인터넷방송통신학회논문지
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• 제15권2호
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• pp.1-7
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• 2015

최근 전 세계적으로 스마트폰의 사용이 급증하고 있으며, 국내의 경우 스마트폰 가입자 수는 약 2400만명으로 전체 이통사의 가입자중 47.7%가 스마트폰을 사용하고 있다. 스마트폰의 경우 보안에 대해 취약점을 가지고 있으며, 스마트폰을 이용한 보안관련 사고피해가 해가 갈수록 증가하고 있다. 그러나 기존의 방식은 사전 대책이 아닌 대부분 사후대책으로써 전문가의 경우를 제외하면 피해를 입은 뒤에 그 피해가 발생한 악성코드의 분석이 이루어지고 있다. 이에 따라 본 논문에서는 가상화 기술을 적용한 모바일 기반의 악성코드분석 시스템을 구현하고 이를 통하여 행위분석을 하도록 설계한다. 가상화는 컴퓨터 리소스의 물리적인 특징을 추상화하여 게스트에게 논리적인 리소스를 제공하는 기술이다. 이러한 가상화 기술은 클라우드 컴퓨팅 서비스와 접목시켜 서버, 네트워크, 스토리지등 컴퓨팅 자원을 탄력적으로 제공함으로 자원의 효율성을 높이고 있다. 아울러 사용자 관점에서 사전에 보안사고를 대비할 수 있는 시스템을 제시한다.

• 한국의류학회지
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• 제20권1호
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• pp.170-182
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• 1996

The purpose of this study is to classify the upper body of women into several kind.; of somatotypes, using the method of Surgical Tape and making their shells. The subjects are 50 females 20 to 29 years-old. Fifty-one anthropometric data are measured per shell of body surface : eight somatotype factors are obtained through principal component analysis and orthogonal rotation by the method of Varimax, Somatotype of women's upper body is achieved by cluster analysis, using the standardized factor score a.: an independent variable and the FASTCLUS of SAS by Kmeans. The results are as follows : 1. The number of the factors which explain the somatotype is eight and these factors comprise 81.63 percent of total variance. Factor 1 related to the degree of fatness in the front of upper body Factor 2 related to the degree of fatness in the back of upper body Factor 3 . related to the length of the upper body Factor 4 : related to the type of the upper chest over the chest circmference line Factor 5 : related to the armhole and neck Factor 6 : related to the type of lower chest under the chest circumference line Factor 7: related to the part of the back shoulder Factor 8: related to the depth of front neck and side dart of front independently 2. Cluster analysis results in classification of upper body into five clusters. Cluster 1 : the of circumference i.: lager and that of length is longer than the average The louver part of chest is the lagest and widest among surface areas. Cluster 2 : the circumference is the smallest , the length and surface area are small. The upper and lower chest is small Cluster 3 : the length and surface area are the smallest , the circumference is average. The body line (silhouette) from chest to waist is curved slightly.

• 한국식생활문화학회지
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• 제25권6호
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• pp.764-769
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• 2010

The aim of this study was to examine how customers perceive storytelling at a real local restaurant and to understand how consumption reflects their evaluation by understanding their values. Participants received information from a real local restaurant in the Gangneung area to examine the effects of storytelling and to evaluate their affective attitudes towards local restaurant stories, word-of-mouth intentions, and purchasing intentions using a seven-point Likert scale. A total of 310 consumers were used. A factor analysis was performed to identify consumption value characteristics and factor structure, which consisted economic value, emotional value, and epistemic value. To test whether local restaurant consumers could be classified into homogenous groups based on their consumption values, a three cluster solution was selected, and a Kmeans cluster analysis was performed. As a result, three groups were identified and labeled appropriate for their scores based on each of the consumption values; emotional value-oriented consumers to cluster 1, epistemic value-oriented consumers to cluster 2, and economic value-oriented consumers to cluster 3. An analysis of variance was used to examine the differences in the affective attitudes towards storytelling at the local restaurant, purchasing intentions, and word-of-mouth intentions across the three clusters. The epistemic value-oriented consumers had the highest score for all three variables. In contrast, economic value-oriented consumers had the lowest scores for the three variables. A regression analysis revealed that affective attitudes towards storytelling were significantly affected by these three consumption values. It also showed that positive affective attitudes towards storytelling were associated with higher purchasing intention and word-of-mouth. The significance of this study was to show how customers perceive storytelling at a real restaurant and reflect on their evaluation by understanding their consumption values. As a result, this study examined the potential power of storytelling as an effective marketing communication tool for local restaurants.

• 대한토목학회논문집
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• 제29권3D호
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• pp.347-356
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• 2009

본 연구는 기존의 도로기능분류 정의와 방법론을 벗어나 교통특성에 따른 도로분류 방법론인 도로특성분류를 기초로 분석을 수행하였다. 도로특성분류에 대한 일련의 과정 중에서 다양한 교통특성을 반영하는 설명변수를 기초로 요인점수를 산출하고, 동질한 도로구간을 그룹핑하는 군집화 분석과정과 적정 군집수 도출에 따른 군집결과비교에 본 연구는 초점을 맞추었다. 도로분류를 위해 병합적 계층 군집분석인 Ward법, 비계층적 군집분석인 K-means법, 자율신경 회로망을 이용한 K-SOM을 사용하여 비교분석하였다. 각 군집기법에 대한 결과를 토대로 비교분석한 결과, 군집 수 5 이하에서는 K-means법, 군집 수 14 이상에서는 Kohonen selforganizing maps가 가장 우수한 것으로 나타났으며, 군집수 5~9사이에서는 Ward법과 Kmeans법의 군집 성능이 불규칙한 패턴을 보임에 따라 세밀한 결과분석을 통해 우수성을 결정하는 것이 바람직할 것으로 분석되었다. 본 연구결과는 다양한 교통특성을 고려한 도로구간의 군집 속성을 분석하고 예측하는 분류화 작업에 중요한 기초적인 자료로 사용될 것으로 기대된다.

• 유통과학연구
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• 제14권1호
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• pp.67-74
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• 2016

Purpose - In this paper, the degree of similarity and dissimilarity between pairs of 50 major cities in China can be shown on the basis of three evaluation variables(internet businessman index, internet shopping index and e-commerce development index). Dissimilarity distance matrix is used to analyze both similarity and dissimilarity between each fifty city in China by calculating dissimilarity as distance. Higher value signifies higher degree of dissimilarity between two cities. Cluster analysis is exploited to classify 50 cities into a number of different groups such that similar cities are placed in the same group. In addition, multidimensional scaling(MDS) technique can obtain visual representation for exploring the pattern of proximities among 50 major cities in China based on three development performance attributes. Research design, data, and methodology - This research is performed by the 2013 report provided with AliResearch in China(1/1/2013~11/30/2013) and utilized multivariate methods such as dissimilarity distance matrix, cluster analysis and MDS by using CLUSTER, KMEANS, PROXIMITIES and ALSCAL procedures in SPSS 21.0. Results - This research applies two types of cluster analysis and MDS on three development performances based on the 2013 report of Aliresearch. As a result, it is confirmed that grouping is possible by categorizing the types into four clusters which share similar characteristics. MDS is exploited to carry out positioning of both grouped locations of cluster and 50 major cities belonging to each cluster. Since all the values corresponding to Shenzhen, Guangzhou and Hangzhou(which belong to cluster 1 among 50 major cities) are very large, these cities are superior to other cities in all three evaluation attributes. Twelve cities(Beijing, ShangHai, Jinghua, ZhuHai, XiaMen, SuZhou, NanJing, DongWan, ZhangShan, JiaXing, NingBo and FoShan), which belong to cluster 3, are inferior to those of cluster 1 in terms of all three attributes, but they can be expected to be the next e-commerce revolution. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three attributes, so that this automatically evokes creative innovation, which leads to e-commerce development as a whole in China. In terms of internet businessman index, on the other hand, Tainan, Taizhong, and Gaoxiong(which belong to cluster 2) are situated superior to others. However, these three cities are inferior to others in an internet shopping index sense. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three evaluation attributes, so that this automatically evokes innovation and entrepreneurship, which leads to e-commerce development as a whole in China. Conclusions - This study suggests the implications to help e-governmental officers and companies make strategies in both Korea and China. This is expected to give some useful information in understanding the recent situation of e-commerce in China, by looking over development performances of 50 major cities. Therefore, we should develop marketing, branding and communication relevant to online Chinese consumers. One of these efforts will be incentives like loyalty points and coupons that can encourage consumers and building in-house logistics networks.

• 한국지구과학회지
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• 제33권4호
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• pp.337-349
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• 2012

본 연구에서는 1000 hPa면 고도 자료 및 K-평균 군집분석법을 활용하여 한반도 주변 기압배치를 분류하고, 각 유형의 특성을 조사하였다. 군집의 기준으로 기압배치 공간 형태의 유사성을 나타내는 패턴 상관계수를 사용하고, 유사성의 경계치로 0.8을 적용하여 대표적 기압배치 유형 11개를 얻었다. 이들은 시베리아 기단이 한반도 주변으로 장출하는 경로에 따라 3개, 북태평양 고기압의 중심 위치에 따라 3개, 시베리아 및 북태평양 기단의 영향권에서 기압골이 나타나는 유형 2개, 그리고 봄가을에 주로 나타나는 이동성 고기압형으로 고기압의 장축방향에 따라 3개 등이다. 각 기압 배치 유형의 출현빈도로부터 추정한 한반도에 영향을 주는 기단의 출현비율은 시베리아 기단 55.4%, 북태평양 기단 29.3%, 양쯔강 기단 12.8%, 오호츠크해 기단 2.5% 순이며, 한반도는 대륙에서 기원한 기단의 영향이 68.2%로 지배적이다. 한반도 주변 기압계는 겨울 기압배치 유형과 여름 기압배치 유형이 각기 대륙과 해양에 발달하는 정체성 기단으로부터 확장되는 고기압을 중심으로 하여 대조적으로 출현하고, 봄가을의 이동성 고기압형은 이들의 변환 과정에서 나타난다. 근래 여름 북태평양 고기압의 한반도 출현빈도가 감소하고 있다. 그리고 겨울 기압배치 유형의 출현이 봄가을에 자주 나타나면서 기압골을 갖는 기압배치 유형의 출현빈도가 증가하고, 이동성 고기압형은 거의 모든 계절에 나타나는 경향이 있다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제7권1호
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• pp.9-18
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• 2018

분산 처리 플랫폼에서 다양한 빅 데이터 처리 어플리케이션들의 수행 성능 향상에 대한 관심이 높아지고 있다. 이에 따라 범용적인 분산 처리 플랫폼인 아파치 스파크에서 어플리케이션들의 처리 성능 최적화에 대한 연구들이 활발하게 진행되고 있다. 스파크에서 데이터 처리 어플리케이션들의 수행 성능을 향상시키기 위해서는 스파크의 분산처리모델인 Directed Acyclic Graph(DAG)에 알맞은 형태로 어플리케이션을 최적화시켜야 하고 어플리케이션의 처리 특징을 고려하여 스파크 시스템 파라미터들을 설정해야 하기 때문에 매우 어렵다. 기존 연구들은 각각의 어플리케이션의 처리 성능에 영향을 주는 하나의 요소에 대한 부분적인 연구를 수행했고, 최종적으로 어플리케이션의 성능개선을 이뤄냈지만 스파크의 전반적인 처리과정을 고려한 성능 최적화를 다루지 않았을 뿐만 아니라 처리성능과 상관관계를 갖는 다양한 요소들의 복합적인 상호작용을 고려하지 못했다. 본 연구에서는 스파크에서 일반적인 데이터 처리 어플리케이션의 수행 과정을 분석하고, 분석된 결과를 토대로 어플리케이션의 처리과정 중 스테이지 내부와 스테이지 사이에서 성능 향상을 위한 처리 전략을 제안한다. 또한 스파크의 시스템 설정 파라미터 중 분산 병렬처리와 밀접한 관계를 갖는 파티션 병렬화에 따른 어플리케이션의 수행성능을 분석하고 적합한 파티셔닝 최적화 기법을 제안한다. 3가지 성능 향상 전략의 실효성을 입증하기 위해 일반적인 데이터 처리 어플리케이션: WordCount, Pagerank, Kmeans에 각각의 방법을 사용했을 때의 성능 향상률을 제시한다. 또한 제안한 3가지 성능 최적화 기법들이 함께 적용될 때 복합적인 성능향상 시너지를 내는지를 확인하기 위해 모든 기법들이 적용됐을 때의 성능 향상률을 제시함으로써 본 연구에서 제시하는 전략들의 실효성을 입증한다.