• Title/Summary/Keyword: cluster method

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Robust Airspeed Estimation of an Unpowered Gliding Vehicle by Using Multiple Model Kalman Filters (다중모델 칼만 필터를 이용한 무추력 비행체의 대기속도 추정)

  • Jin, Jae-Hyun;Park, Jung-Woo;Kim, Bu-Min;Kim, Byoung-Soo;Lee, Eun-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.8
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    • pp.859-866
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    • 2009
  • The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

Studies on the Structure of Forest Community at Taech'ongbong-Soch'ongbong Area in Soraksan National Park (설악산 국립공원 대청봉-소청봉 지역의 삼림군집구조에 관한 연구)

  • 김갑태;엄태원;추갑철
    • Korean Journal of Environment and Ecology
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    • v.10 no.2
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    • pp.240-250
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    • 1997
  • To investigate the structure and the conservation strategy of natural forest at Soch'ongbong-Taech'ongbong Area in Soraksan , 36 plots (20m*20) set up with random sampling method. Three groups - Quercus mongolica- Abies holophylla community, Acer mandshuricum- Abies nebhrolepis community, Abies holophylla-Ulmus laciniata-were classified by cluster analysis. High positive correlations were proved between Ulmus laciniata and Carpinus cordata; Tripterygium regelii and Syringa reticulata var. mandshurica ; Tripterygium regelii and Rhodo- dendron brachycarpum ; Carpinus cordata and Rhododenron mucronulatm; Wergela subsessilis and Rhododenron nucronulatum and High negative correlations were proved between Rhododen- dron schippenbachii and Euonymus macroptera; Betula ermani and Acer pseudo-sieboldianum, Tilia amurensis, Magnolia sieboldii, Betula costata ; Pinus pumila and Pinus koraiensis. Species diversity(H') of investigated area was calculated 0.8393~1.3431.

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Anchor Frame Detection Using Anchor Object Extraction (앵커 객체 추출을 이용한 앵커 프레임 검출)

  • Park Ki-Tae;Hwang Doo-Sun;Moon Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.3 s.309
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    • pp.17-24
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    • 2006
  • In this paper, an algorithm for anchor frame detection in news video is proposed, which consists of four steps. In the first step, the cumulative histogram method is used to detect shot boundaries in order to segment a news video into video shots. In the second step, skin color information is used to detect face regions in each shot boundary. In the third step, color information of upper body regions is used to extract anchor object, which produces candidate anchor frames. Then, from the candidate anchor frames, a graph-theoretic cluster analysis algorithm is utilized to classify the news video into anchor-person frames and non-anchor frames. Experiment results have shown the effectiveness of the proposed algorithm.

Energy Modeling For the Cluster-based Sensor Networks (클러스터 기반 센서 네트워크의 에너지 모델링 기법)

  • Choi, Jin-Chul;Lee, Chae-Woo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.3
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    • pp.14-22
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    • 2007
  • Wireless sensor networks are composed of numerous sensor nodes and exchange or recharging of the battery is impossible after deployment. Thus, sonsor nodes must be very energy-efficient. As neighboring sensor nodes generally have the data of similar information, duplicate transmission of similar information is usual. To prevent energy wastes by duplicate transmissions, it is advantageous to organize sensors into clusters. The performance of clustering scheme is influenced by the cluster-head election method and the size or the number of clusters. Thus, we should optimize these factors to maximize the energy efficiency of the clustering scheme. In this paper, we propose a new energy consumption model for LEACH which is a well-known clustering protocol and determine the optimal number of clusters based on our model. Our model has accuracy over 80% compared with the simulation and is considerably superior to the existing model of LEACH.

Identifying the Optimal Number of Homogeneous Regions for Regional Frequency Analysis Using Self-Organizing Map (자기조직화지도를 활용한 동일강수지역 최적군집수 분석)

  • Kim, Hyun Uk;Sohn, Chul;Han, Sang-Ok
    • Spatial Information Research
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    • v.20 no.6
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    • pp.13-21
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    • 2012
  • In this study, homogeneous regions for regional frequency analysis were identified using rainfall data from 61 observation points in Korea. The used data were gathered from 1980 to 2010. Self organizing map and K-means clustering based on Davies-Bouldin Index were used to make clusters showing similar rainfall patterns and to decide the optimum number of the homogeneous regions. The results from this analysis showed that the 61 observation points can be optimally grouped into 6 geographical clusters. Finally, the 61 observations points grouped into 6 clusters were mapped regionally using Thiessen polygon method.

Forest Type Classification and Successional Trends in the Natural Forest of Mt. Deogyu (덕유산 일대 천연림의 산림형 분류와 천이경향)

  • Hwang, Kwang Mo;Chung, Sang Hoon;Kim, Ji Hong
    • Journal of Korean Society of Forest Science
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    • v.105 no.2
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    • pp.157-166
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    • 2016
  • This study was carried out to classify the current forest cover types and to propose the successional trends in the natural forest of Mt. Deogyu. The vegetation data were collected by the point-centered quarter method. The forest cover types were classified by various multivariate statistical analysis methods such as cluster analysis, indicator species analysis and multiple discriminant analysis. This forests were classified into five forest types by the species composition of upper layer and topographic positions: Quercus mongolica forest in the ridge, Fraxinus mandushurica-F. rhynchophylla-Cornus controversa forest and F. mandushurica forest in the valley, the Q. serrata - Pinus densiflora - Q. mongolica forest and P. densiflora forest in the low-slope. As a result of the forest successional trends depending on ecological and environmental characteristics in each forest type, the current forest types were expected that the forest succession would be proceeded toward Q. mongolica forest, F. mandshurica forest, mixed mesophytic forest, and oak-Carpinus laxiflora forest.

A study on Life Style and Clothing Involvement of Elderly Women (노년기 여성의 라이프 스타일과 의복관여에 관한 연구)

  • 이은실;이명희
    • Journal of the Korean Society of Costume
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    • v.25
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    • pp.233-247
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    • 1995
  • The objectives of this study were to classify the contents of clothing involvement, to group elderly women into life style types. A method of this study was face to face re-search and questionnaire. Questionnaire was comprised of four sections : 18 Likert type items of clothing involvement measure ; 26 Likert type items of life style measure ; 3 items of clothing purchase measure ; and 3 demographic variables. Samples were 215 elderly women(60∼79 years of age) in Seoul, Korea. The data were analyzed using factor analy-sis, cluster analysis, one-way ANOVA, Dun-can's multiple range test,χ2 test. The results of the study were the follow-ings. 1. Four factors of clothing involvement derived by factor analysis : F.1 'clothing pleasure'; F.2 'clothing symbolism' ; F.3 'perceived risk in clothing purchase' ; F.4 'clothing interest'. 2. Four factors of life style derived by factor analysis : F.1 'active-leisure';F.2 'confidence oriented';F.3 'appearance interest';F.4 'house-work interest and community conciousness'. Three types of life style were defined by the cluster analysis of the 4 factors : T.1 'passive stag-nation'; T.3'outside activity'. 3. There were significant differences in clothing involvement factors according to life style types. Outside activity type perceived 'clothing pleasure' highest level among 3 life style types. Outside activity type and house-work and positive living type perceived 'cloth-ing symbolism' and 'clothing interest' higher level than did passive stagnation types. 4. Elderly women high in educational level were more distributed in outside activity type and the low in educational level in passive stagnation types. 5. There were significant relationships be-tween life style types and source of a clothing allowance, clothing purchase frequency, and a companion of dress store.

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Upper Body-Type Classification of Jeonbuk Women in Their Twenties (전북 거주 20대 여성의 상의원형개발을 위한 상반신 체형연구)

  • Kim, Ju-Yeon;Lee, Hyo-Jin
    • Journal of the Korean Society of Costume
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    • v.63 no.1
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    • pp.97-107
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    • 2013
  • To give satisfaction with the fit to a wearer, the wearer's body size and body types should be considered first, this study conducted the descriptive statistical analysis on the upper body measurements of women in their 20s because their body shape has reached the completion stage of adult female's physical development. Also, the analysis classified their upper body types into groups to secure basic data for (maximum satisfaction with the fit of ready-to-wear clothing. The factor analysis was conducted using 49 items of measurement. The main factor analysis was used as a factor extraction method. After extracting the factors with Eigenevalues over 1, the factor loadings were drawn using the Varimax rotation. As a result, 6 factors were extracted. To secure internal consistency, factors that could lower the reliability of the experiment were taken out, so only 36 of the 49 items were used for the analysis. After selecting the items to recognize the main features of each body type, they were used for the final factor analysis. The entire R square of the 6 factors was 84.06%. To classify the upper body types of women in their 20s and to recognize the main features of each body shape type, the researcher conducted the cluster analysis with the items generated from the factor analysis. Through the cluster analysis, the upper body type of women in their 20s were classified into 3 body types. Also, since there are some restrictions on this research objects in terms of local and numbers of measured objects, the results of the this research should only be used as basic data.

Examining the Intellectual Structure of Records Management & Archival Science in Korea with Text Mining (텍스트 마이닝을 이용한 국내 기록관리학 분야 지적구조 분석)

  • Lee, Jae-Yun;Moon, Ju-Young;Kim, Hee-Jung
    • Journal of the Korean Society for Library and Information Science
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    • v.41 no.1
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    • pp.345-372
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    • 2007
  • In this study, the intellectual structure of Records Management & Archival Science in Korea was analyzed using document clustering, a widely used method of text mining, and document similarity network analysis. The data used in this study were 145 articles written on the subject of Records Management & Archival Science selected from five major representative journals in the field of Library & Information Science in Korea, published from 2001 to 2006. The results of cluster analysis show that the core subject areas are "electronic records management and digital Preservation," "records management policy and institution," "records description and catalogues." and "records management domain and education." The results of document analysis, which is more detailed than cluster analysis, show that "digital archiving," a specialized subject in digital preservation, plays a central role. The results of serial analysis, which proceeds according to a timeline, show the emergence of "archival services" as a new subject area.

Assessment of Population Structure and Genetic Diversity of 15 Chinese Indigenous Chicken Breeds Using Microsatellite Markers

  • Chen, Guohong;Bao, Wenbin;Shu, Jingting;Ji, Congliang;Wang, Minqiang;Eding, Herwin;Muchadeyi, Farai;Weigend, Steffen
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.3
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    • pp.331-339
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    • 2008
  • The genetic structure and diversity of 15 Chinese indigenous chicken breeds was investigated using 29 microsatellite markers. The total number of birds examined was 542, on average 36 birds per breed. A total of 277 alleles (mean number 9.55 alleles per locus, ranging from 2 to 25) was observed. All populations showed high levels of heterozygosity with the lowest estimate of 0.440 for the Gushi chickens, and the highest one of 0.644 observed for Wannan Three-yellow chickens. The global heterozygote deficit across all populations (FIT) amounted to 0.180 (p<0.001). About 16% of the total genetic variability originated from differences between breeds, with all loci contributing significantly to this differentiation. An unrooted consensus tree was constructed using the Neighbour-Joining method and pair-wise distances based on marker estimated kinships. Two main groups were found. The heavy-body type populations grouped together in one cluster while the light-body type populations formed the second cluster. The STRUCTURE software was used to assess genetic clustering of these chicken breeds. Similar to the phylogenetic analysis, the heavy-body type and light-body type populations separated first. Clustering analysis provided an accurate representation of the current genetic relations among the breeds. Remarkably similar breed rankings were obtained with all methods.