• Title/Summary/Keyword: Data Clustering

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Distribution of Invasive Species in Metropolitan Busan, South Korea (생태계교란식물의 부산광역시 분포 실태)

  • Ryu, Tae-Bok;Lim, Jeong-Cheol;Lee, Cheol-Ho;Kim, Eui-Ju;Choi, Byoung-Ki
    • Journal of Life Science
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    • v.27 no.4
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    • pp.408-416
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    • 2017
  • This research aimed to identify the diversity and the distribution of invasive alien plant species in the metropolitan city of Busan, South Korea. According to our results, we discovered 10 species of invasive alien plants distributed in Busan, demonstrating that this urban area has a high domestic plant diversity. A cluster analysis identified that the dominant communities of Aster pilosus, Lactuca serriola, Ambrosia artemisiifolia, Rumex acetosella and Solanum carolinense were highly similar in species composition. Different species of invasive alien plants tended to occur together in dominant communities, indicating their preference for shared habitats. The most extensively distributed species in Busan were Lactuca serriola (16 districts), followed by Ambrosia artemisiifolia (11 districts), Aster pilosus (11 districts) and Rumex acetosella (10 districts). The administrative districts with the most diverse invasive alien plants were Gangseo-gu (8 species) and Buk-gu (8 species), which are both areas with high human interference and diverse habitats. Additional environmental information was collected for these species' habitats in Busan. The results of this research can be used to assess the current status of invasive alien plants in Busan and can provide basic data useful for effectively controlling and preventing the spread of invasive plants.

Delineation of Provenance Regions of Forests Based on Climate Factors in Korea (기상인자(氣象因子)에 의한 우리 나라 산림(山林)의 산지구분(産地區分))

  • Choi, Wan Yong;Tak, Woo Sik;Yim, Kyong Bin;Jang, Suk Seong
    • Journal of Korean Society of Forest Science
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    • v.88 no.3
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    • pp.379-388
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    • 1999
  • As a first step for delineating the provenance regions of the forest trees in Korea, horizontal zones have been deduced primarily from the various climatic factors such as annual mean temperature, extremely low temperature, relative humidity, annual gum of possible growing days, duration of sunshine and dry index. The basic concept to the delineation of the provenance regions was based on the ecological regions, which was likely to be more practical than that on the basis of the typical provenance regions at the species level. Primary classification of the regions has been based on the forest zones(sub-tropical, warm-temperate, mid-temperate and cool-temperate) as a broad geographic region. Further classification has been carried out using cluster analyses among the basic regions within forest zone. On the basis of clustering, a total of 19 regions including 3 from sub-tropical, 6 from warm-temperate, 8 from mid-temperate and 2 from cool-temperate was horizontally delineated. Of the mean values of 6 climate factors at the broad geographic region level, three factors such as annual mean temperature, extremely low temperature, annual growing days showed directional tendencies from subtropical to cool-temperate, while the others didn't. The values of relative humidity, duration of sunshine and dry index varied among the provenance regions within forest zone. These three factors might he more sensitive by the micro-environment condition than by the macro-environment condition. Present study aimed to delineate the primary provenance regions for tentative application to forest practices. These will be stepwise revised through the supplement using accumulated information regard to genecological data.

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Syntaxonomy and Synecology of the Robinia pseudoacacia Forests (아까시나무림의 군락분류와 군락생태)

  • Cho, Kwang-Jin;Kim, Jong-Won
    • The Korean Journal of Ecology
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    • v.28 no.1
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    • pp.15-23
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    • 2005
  • The black locust (Robinia pseudoacacia L.) forests were studied by a phytosociological approach. Particular attention was given to characterize the vegetation classification, distribution pattern, and ecological flora of the syntaxa classified. A total of 38 releves were analyzed by using Correlation coefficient, UPGMA as the clustering method, and Principal Coordinates Analysis for ordination. Ecological flora analyzed by plant character sets such as scrambler, annual and biennial plants, forest elements, and actual urbanization index. The analyzed data are based on site-releve matrix with relative net contribution degree (r-NCD) of species. A total of 77 families, 193 genera and 323 species of vascular plants are recorded. Camellino-Robinietum pseudoacaciae ass. nov. and Phragmites-Robinia pseudoacacia community were described. Main cluster and ordination could be separated: 1) urban type, 2) rural type, 3) riparian type, and 4) combined type. It is defined that the Robinietum is a representative unit on the black locust afforestation, Phragmites-Robinia community on the lentic zone in the river ecosystem, and Cameliino-Robinietum ailanthetosum altissimae as an urban forest type. The Robinietum was considered as a perpetual community.

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.

Assessing Water Quality of Siheung Stream in Shihwa Industrial Complex Using Both Principal Component Analysis and Multi-Dimensional Scaling Analysis of Korean Water Quality Index and Microbial Community Data (Principal Component Analysis와 Multi-Dimensional Scaling 분석을 이용한 시화공단 시흥천의 수질지표 및 미생물 군집 분포 연구)

  • Seo, Kyeong-Jin;Kim, Ju-Mi;Kim, Min-Jung;Kim, Seong-Keun;Lee, Ji-Eun;Kim, In-Young;Zoh, Kyung-Duk;Ko, Gwang-Pyo
    • Journal of Environmental Health Sciences
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    • v.35 no.6
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    • pp.517-525
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    • 2009
  • The water quality of Lake Shihwa had been rapidly deteriorating since 1994 due to wastewater input from the watersheds, limited water circulation and the lack of a wastewater treatment policy. In 2000, the government decided to open the tidal embankment and make a comprehensive management plan to improve the water quality, especially inflowing stream water around Shihwa and Banwol industrial complex. However, the water quality and microbial community have not as yet been fully evaluated. The purpose of this study is to investigate the influent water quality around the industrial area based on chemical and biological analysis, and collected surface water sample from the Siheung Stream, up-stream to down-stream through the industrial complex, Samples were collected in July 2009. The results show that the downstream site near the industrial complex had higher concentrations of heavy metals (Cu, Mn, Fe, Mg, and Zn) and organic matter than upstream sites. A combination of DGGE (Denaturing Gradient Gel Electrophoresis) gels, lists of K-WQI (Korean Water Quality Index), cluster analysis, MDS (Multi-Dimensional Scaling) and PCA (Principal Component Analysis) has demonstrated clear clustering between Siheung stream 3 and 4 and with a high similarity and detected metal reducing bacteria (Shewanella spp.) and biodegrading bacteria (Acinetobacter spp.). These results suggest that use of both chemical and microbiological marker would be useful to fully evaluate the water quality.

Design of Optimized pRBFNNs-based Face Recognition Algorithm Using Two-dimensional Image and ASM Algorithm (최적 pRBFNNs 패턴분류기 기반 2차원 영상과 ASM 알고리즘을 이용한 얼굴인식 알고리즘 설계)

  • Oh, Sung-Kwun;Ma, Chang-Min;Yoo, Sung-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.749-754
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    • 2011
  • In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

Facilitating Web Service Taxonomy Generation : An Artificial Neural Network based Framework, A Prototype Systems, and Evaluation (인공신경망 기반 웹서비스 분류체계 생성 프레임워크의 실증적 평가)

  • Hwang, You-Sub
    • Journal of Intelligence and Information Systems
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    • v.16 no.2
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    • pp.33-54
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    • 2010
  • The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

The Effect of Lidocaine.HCl on the Fluidity of Native and Model Membrane Lipid Bilayers

  • Park, Jun-Seop;Jung, Tae-Sang;Noh, Yang-Ho;Kim, Woo-Sung;Park, Won-Ick;Kim, Young-Soo;Chung, In-Kyo;Sohn, Uy Dong;Bae, Soo-Kyung;Bae, Moon-Kyoung;Jang, Hye-Ock;Yun, Il
    • The Korean Journal of Physiology and Pharmacology
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    • v.16 no.6
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    • pp.413-422
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    • 2012
  • The purpose of this study is to investigated the mechanism of pharmacological action of local anesthetic and provide the basic information about the development of new effective local anesthetics. Fluorescent probe techniques were used to evaluate the effect of lidocaine HCl on the physical properties (transbilayer asymmetric lateral and rotational mobility, annular lipid fluidity and protein distribution) of synaptosomal plasma membrane vesicles (SPMV) isolated from bovine cerebral cortex, and liposomes of total lipids (SPMVTL) and phospholipids (SPMVPL) extracted from the SPMV. An experimental procedure was used based on selective quenching of 1,3-di(1-pyrenyl)propane (Py-3-Py) and 1,6-diphenyl-1,3,5-hexatriene (DPH) by trinitrophenyl groups, and radiationless energy transfer from the tryptophans of membrane proteins to Py-3-Py. Lidocaine HCl increased the bulk lateral and rotational mobility of neuronal and model membrane lipid bilayes, and had a greater fluidizing effect on the inner monolayer than the outer monolayer. Lidocaine HCl increased annular lipid fluidity in SPMV lipid bilayers. It also caused membrane proteins to cluster. The most important finding of this study is that there is far greater increase in annular lipid fluidity than that in lateral and rotational mobilities by lidocaine HCl. Lidocaine HCl alters the stereo or dynamics of the proteins in the lipid bilayers by combining with lipids, especially with the annular lipids. In conclusion, the present data suggest that lidocaine, in addition to its direct interaction with proteins, concurrently interacts with membrane lipids, fluidizing the membrane, and thus inducing conformational changes of proteins known to be intimately associated with membrane lipid.

Group Classification on Management Behavior of Diabetic Mellitus (당뇨 환자의 관리행태에 대한 군집 분류)

  • Kang, Sung-Hong;Choi, Soon-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.2
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    • pp.765-774
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    • 2011
  • The purpose of this study is to provide informative statistics which can be used for effective Diabetes Management Programs. We collected and analyzed the data of 666 diabetic people who had participated in Korean National Health and Nutrition Examination Survey in 2007 and 2008. Group classification on management behavior of Diabetic Mellitus is based on the K-means clustering method. The Decision Tree method and Multiple Regression Analysis were used to study factors of the management behavior of Diabetic Mellitus. Diabetic people were largely classified into three categories: Health Behavior Program Group, Focused Management Program Group, and Complication Test Program Group. First, Health Behavior Program Group means that even though drug therapy and complication test are being well performed, people should still need to improve their health behavior such as exercising regularly and avoid drinking and smoking. Second, Focused Management Program Group means that they show an uncooperative attitude about treatment and complication test and also take a passive action to improve their health behavior. Third, Complication Test Program Group means that they take a positive attitude about treatment and improving their health behavior but they pay no attention to complication test to detect acute and chronic disease early. The main factor for group classification was to prove whether they have hyperlipidemia or not. This varied widely with an individual's gender, income, age, occupation, and self rated health. To improve the rate of diabetic management, specialized diabetic management programs should be applied depending on each group's character.

A Semi-Noniterative VQ Design Algorithm for Text Dependent Speaker Recognition (문맥종속 화자인식을 위한 준비반복 벡터 양자기 설계 알고리즘)

  • Lim, Dong-Chul;Lee, Haing-Sei
    • The KIPS Transactions:PartB
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    • v.10B no.1
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    • pp.67-72
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    • 2003
  • In this paper, we study the enhancement of VQ (Vector Quantization) design for text dependent speaker recognition. In a concrete way, we present the non-Iterative method which makes a vector quantization codebook and this method Is nut Iterative learning so that the computational complexity is epochally reduced. The proposed semi-noniterative VQ design method contrasts with the existing design method which uses the iterative learning algorithm for every training speaker. The characteristics of a semi-noniterative VQ design is as follows. First, the proposed method performs the iterative learning only for the reference speaker, but the existing method performs the iterative learning for every speaker. Second, the quantization region of the non-reference speaker is equivalent for a quantization region of the reference speaker. And the quantization point of the non-reference speaker is the optimal point for the statistical distribution of the non-reference speaker In the numerical experiment, we use the 12th met-cepstrum feature vectors of 20 speakers and compare it with the existing method, changing the codebook size from 2 to 32. The recognition rate of the proposed method is 100% for suitable codebook size and adequate training data. It is equal to the recognition rate of the existing method. Therefore the proposed semi-noniterative VQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal.