• Title/Summary/Keyword: 3D Clustering

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An Intelligent Monitoring System of Semiconductor Processing Equipment using Multiple Time-Series Pattern Recognition (다중 시계열 패턴인식을 이용한 반도체 생산장치의 지능형 감시시스템)

  • Lee, Joong-Jae;Kwon, O-Bum;Kim, Gye-Young
    • The KIPS Transactions:PartD
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    • v.11D no.3
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    • pp.709-716
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    • 2004
  • This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

An Efficiency Analysis of Industry-University-Public Research Institute Collaborative Research: Employing the Input-Output Itemization Model (투입 및 산출 분해모형을 활용한 산학연 협력연구의 효율성 분석)

  • Kim, Hong-Young;Chung, Sunyang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.12
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    • pp.473-484
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    • 2017
  • This study analyzed collaborative R&D projects funded by the Korean government from 2013-2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader's organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.

Study of Structure Modeling from Terrestrial LIDAR Data (지상라이다 데이터를 이용한 구조물 모델링 기법 연구)

  • Lee, Kyung-Keun;Jung, Kyeong-Hoon;Kim, Ki-Doo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.8-15
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    • 2011
  • In this paper, we propose a new structure modeling algorithm from 3D cloud points of terrestrial LADAR data. Terrestrial LIDAR data have various obstacles which make it difficult to apply conventional algorithms designed for air-borne LIDAR data. In the proposed algorithm, the field data are separated into several clusters by adopting the structure extraction method which uses color information and Hough transform. And cluster based Delaunay triangulation technique is sequentially applied to model the artificial structure. Each cluster has its own priority and it makes possible to determine whether a cluster needs to be considered not. The proposed algorithm not only minimizes the effects of noise data but also interactively controls the level of modeling by using cluster-based approach.

Effects of Baicalin on Gene Expression Profiles during Adipogenesis of 3T3-L1 Cells (3T3-L1 세포의 지방세포형성과정에서 Baicalin에 의한 유전자 발현 프로파일 분석)

  • Lee, Hae-Yong;Kang, Ryun-Hwa;Chung, Sang-In;Cho, Soo-Hyun;Yoon, Yoo-Sik
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.39 no.1
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    • pp.54-63
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    • 2010
  • Baicalin, a flavonoid, was shown to have diverse effects such as anti-inflammatory, anti-cancer, anti-viral, anti-bacterial and others. Recently, we found that the baicalin inhibits adipogenesis through the modulations of anti-adipogenic and pro-adipogenic factors of the adipogenesis pathway. In the present study, we further characterized the molecular mechanism of the anti-adipogenic effect of baicalin using microarray technology. Microarray analyses were conducted to analyze the gene expression profiles during the differentiation time course (0 day, 2 day, 4 day and 7 day) in 3T3-L1 cells with or without baicalin treatment. We identified a total of 3972 genes of which expressions were changed more than 2 fold. These 3972 genes were further analyzed using hierarchical clustering analysis, resulting in 20 clusters. Four clusters among 20 showed clearly up-regulated expression patterns (cluster 8 and cluster 10) or clearly down-regulated expression patterns (cluster 12 and cluster 14) by baicalin treatment for over-all differentiation period. The cluster 8 and cluster 10 included many genes which enhance cell proliferation or inhibit adipogenesis. On the other hand, the cluster 12 and cluster 14 included many genes which are related with proliferation inhibition, cell cycle arrest, cell growth suppression or adipogenesis induction. In conclusion, these data provide detailed information on the molecular mechanism of baicalin-induced inhibition of adipogenesis.

Competition - Ecological Classification of the Prominent Paddy Weed Species around Bulrush(Scirpus juncoides) (올챙고랭이(Scirpus juncoides)를 중심으로 한 주요(主要) 논 잡초종(雜草種)의 벼 경합생태적(競合生態的) 분류(分類))

  • Guh, J.O.;Heo, S.M.
    • Korean Journal of Weed Science
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    • v.5 no.2
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    • pp.96-102
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    • 1985
  • A study on the competition-ecological classification of the 10 prominent paddy weed species around bulrush (Scirpus juneoides) to simplify the weed problem concept for the rice production. A serial assessments on the competition ability in space and dry matter production(nutrient depletion) of respective weed species and paddy rice, and the data were used to compute the phenotypic similarity by Single Link Clustering method. Both growth response of weed species in mono- and under the paddy rice standing was very similar (r = 0.969), but the reduction rate as affected by paddy rice standing was negatively correlated with the ability in space-competition(r=-0.513). Dendrogram of 10 weed species based on the phenotypic similarity computed in 4 characters in mono- and under the paddy rice standing was also similar, as Echinochloa c., Ludwigia p., Cyperus s., and Scirpus m. in I-group, Eleocharis k., Scirpus j, in II-group, and Juncus e., Potamogeton d. in III-group, respectively. Also, that of paddy rice to 10 weed species showed Fimbristylis m., Scirpus j., Eleocharis k., Scirpus m., Juncus e. in I-group, and Ludwigia p., Potamogeton d., Monochoria v. in II-group, respectively. The integrated dendrogram by the above two data indicate the I-group with Fimbristylis m., Scirpus j., Eleocharis k. and Juncus e., as higher growth response with relatively lower competition ability to paddy rice, II-group with Cyperus s., Echinochloa c., Potamogeton d., and Ludwigia p., as higher both in growth and competition, and the last, III-group with Monochoria v., and Scirpus m., as lower growth but higher competition, respectively.

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Grouping Preferred Sensations of College Students Using Sementic Differential Methods of Sensation Words (선호감성 어휘분석을 통한 남녀 대학생의 감성 유형화)

  • 나영주;조길수
    • Science of Emotion and Sensibility
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    • v.5 no.1
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    • pp.9-16
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    • 2002
  • This study was designed to cluster the preferred sensibilities of college students, and to distinguish the most preferred sensibility according to gender and their inter-subject differences. 98 of sensibility adjectives were composed into questionnaire with SD method and the data of 176 students were analyzed in ANOVA, Cluster and Correspondence analysis using SAS package. College students were divided into 10-sensibility clusters: the Casual(no-decoration casual, cool-dynamic casual and elaborate-clean casual), the Romantic Modem, the Simple Natural, the Classic(craft-romantic classic and monotonous classic), the Expressionless, the Gorgeous, and the Traditional Folklore. The adjectives and the sensibility clusters of students were visualized together into 2-D with two axis of static vs. dynamic and light vs. heavy.

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Discrimination of Korean Native Chicken Lines Using Fifteen Selected Microsatellite Markers

  • Seo, D.W.;Hoque, M.R.;Choi, N.R.;Sultana, H.;Park, H.B.;Heo, K.N.;Kang, B.S.;Lim, H.T.;Lee, S.H.;Jo, C.;Lee, J.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.26 no.3
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    • pp.316-322
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    • 2013
  • In order to evaluate the genetic diversity and discrimination among five Korean native chicken lines, a total of 86 individuals were genotyped using 150 microsatellite (MS) markers, and 15 highly polymorphic MS markers were selected. Based on the highest value of the number of alleles, the expected heterozygosity (He) and polymorphic information content (PIC) for the selected markers ranged from 6 to 12, 0.466 to 0.852, 0.709 to 0.882 and 0.648 to 0.865, respectively. Using these markers, the calculated genetic distance (Fst), the heterozygote deficit among chicken lines (Fit) and the heterozygote deficit within chicken line (Fis) values ranged from 0.0309 to 0.2473, 0.0013 to 0.4513 and -0.1002 to 0.271, respectively. The expected probability of identity values in random individuals (PI), random half-sib ($PI_{half-sibs}$) and random sibs ($PI_{sibs}$) were estimated at $7.98{\times}10^{-29}$, $2.88{\times}10^{-20}$ and $1.25{\times}10^{-08}$, respectively, indicating that these markers can be used for traceability systems in Korean native chickens. The unrooted phylogenetic neighbor-joining (NJ) tree was constructed using 15 MS markers that clearly differentiated among the five native chicken lines. Also, the structure was estimated by the individual clustering with the K value of 5. The selected 15 MS markers were found to be useful for the conservation, breeding plan, and traceability system in Korean native chickens.

Classification of Terrestrial LiDAR Data Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 지상 라이다 자료의 분류)

  • Choi, Seung-Pil;Cho, Ji-Hyun;Kim, Yeol;Kim, Jun-Seong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.139-144
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    • 2011
  • This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

The Effects of Pilates' Instructors Professionalism on Physical Self-perception and Psychological Happiness (필라테스지도자의 전문성이 신체적자기지각과 심리적행복감에 미치는 영향)

  • Seo, Soo-Jin
    • Journal of Digital Convergence
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    • v.17 no.10
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    • pp.489-496
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    • 2019
  • The purpose of this study was to identify the effects of Pilates' expertise on physical self perception and psychological happiness among adults who participated in the Pilates movement for more than one year. From March 1, 2019 to May 30, 2019, a total of 262 Pilates participants in D and C cities were sampled using the Collective Clustering method. The STSS Ver20.0 statistics program was used to solve the research problem. The study found that first, there were no significant differences in physical self perception and that health had a negative effect on the body's emphasis on the body's neutral and that physical ability had a significant effect on Neutral emphasis on body and Member management. Second, the enjoyment of psychological happiness showed significant differences in An understanding of anatomical knowledge, instructors 'Attitudes, and membership management, while the confidence of psychological happiness showed significant differences in Neutral emphasis on body and Member management. This study shows that the Pilates leader's professionalism has a positive influence on participants and has contributed to presenting basic information regarding various variables.

Development of GK2A Convective Initiation Algorithm for Localized Torrential Rainfall Monitoring (국지성 집중호우 감시를 위한 천리안위성 2A호 대류운 전조 탐지 알고리즘 개발)

  • Park, Hye-In;Chung, Sung-Rae;Park, Ki-Hong;Moon, Jae-In
    • Atmosphere
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    • v.31 no.5
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    • pp.489-510
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    • 2021
  • In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.