• 제목/요약/키워드: Wide Area Classification

검색결과 78건 처리시간 0.024초

멀티미디어 이동통신서비스를 위한 주파수 수요예측 모형 (Frequency Forecasting Model for Next Wireless Multimedia Services)

  • 장희선;한성수;여재현;최성호
    • 산업공학
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    • 제18권3호
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    • pp.333-342
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    • 2005
  • In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group and its applications are presented.

양산 단층곡 경주 지역의 단층 지형 분석 (Analysis on Fault-Related Landformsin the Gyeongju Area of the Yangsan Fault Valley)

  • 박충선;이광률
    • 한국지형학회지
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    • 제25권1호
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    • pp.19-30
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    • 2018
  • This study tries to infer fault lines and produce a map for the lines based on a classification of fault-related landforms and fluvial landformsin the Gyeongju area of the Yangsan Fault Valley. Fault activities in the study area are thought to be older than the time of river formation or stronger than the erosion by river, while the northern and southern parts of the study area seem to have experienced fault activities after valley formation. It is also possible that weaker fault activities than the erosion by river seem to have been prevailed in the parts. In the study area, the Gyeongju alluvial fan is located within a wide erosional valley at the joint area of the Yangsan and Ulsan Faults. From the distribution of the landforms, it is inferred that several fault lines parallel to the Yangsan Fault are distributed at both sides of the fault valley. In particular, the area from Bae-dong to Nogok-ri, Naenam-myeon shows the most obvious linearity of the landforms within the study area. Several fault lines with a direction of NNE-SSW are also found around the epicenter of the 2016 Gyeongju Earthquake.

다변수통계방법을 이용한 산지분류에 관한 연구 (A Study on Forest Land Classification Using Multivariate Statistical Methods : A Case Study at Mt. Kwanak)

  • 정순오
    • 한국조경학회지
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    • 제13권1호
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    • pp.43-66
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    • 1985
  • Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

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Classification of Daily Precipitation Patterns in South Korea using Mutivariate Statistical Methods

  • Mika, Janos;Kim, Baek-Jo;Park, Jong-Kil
    • 한국환경과학회지
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    • 제15권12호
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    • pp.1125-1139
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    • 2006
  • The cluster analysis of diurnal precipitation patterns is performed by using daily precipitation of 59 stations in South Korea from 1973 to 1996 in four seasons of each year. Four seasons are shifted forward by 15 days compared to the general ones. Number of clusters are 15 in winter, 16 in spring and autumn, and 26 in summer, respectively. One of the classes is the totally dry day in each season, indicating that precipitation is never observed at any station. This is treated separately in this study. Distribution of the days among the clusters is rather uneven with rather low area-mean precipitation occurring most frequently. These 4 (seasons)$\times$2 (wet and dry days) classes represent more than the half (59 %) of all days of the year. On the other hand, even the smallest seasonal clusters show at least $5\sim9$ members in the 24 years (1973-1996) period of classification. The cluster analysis is directly performed for the major $5\sim8$ non-correlated coefficients of the diurnal precipitation patterns obtained by factor analysis In order to consider the spatial correlation. More specifically, hierarchical clustering based on Euclidean distance and Ward's method of agglomeration is applied. The relative variance explained by the clustering is as high as average (63%) with better capability in spring (66%) and winter (69 %), but lower than average in autumn (60%) and summer (59%). Through applying weighted relative variances, i.e. dividing the squared deviations by the cluster averages, we obtain even better values, i.e 78 % in average, compared to the same index without clustering. This means that the highest variance remains in the clusters with more precipitation. Besides all statistics necessary for the validation of the final classification, 4 cluster centers are mapped for each season to illustrate the range of typical extremities, paired according to their area mean precipitation or negative pattern correlation. Possible alternatives of the performed classification and reasons for their rejection are also discussed with inclusion of a wide spectrum of recommended applications.

3차원 인체 측정치들을 이용한 중년 여성의 유방 형태에 따른 유형 (Classification of Middle Aged Women's Breast Shapes Using 3D Body Measurement Data)

  • 이현영;홍경희
    • 한국의류학회지
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    • 제34권3호
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    • pp.385-392
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    • 2010
  • The breast types of middle-aged women of 80A (formerly 80B) size were classified through a 3D scanned nude body. Thirty seven measurements including the radius of curvature, surface area, volume, surface length, and breast displacements were used as input variables. We extracted five main factors through the factor analysis of the measurements and classified 36 subjects into 3 clusters through the cluster analysis. As a result of the factor analysis, the size of the breast, breast sag, the curvature of the inner and the outer breast curve, the width of the breast, and the nipple direction were found as the main factors. For the results of the classification of breast types, Cluster 1 was characterized by narrow breast width and unsymmetrical under the breast curve, whereas Cluster 2 was a wide and sagged shape. Cluster 3 was classified into big breast volume and symmetrical under-breast curve. The results are useful to the product development of high quality brassieres which reflect the 3D characteristics of breast types of middle-aged women.

VARIOGRAM-BASED URBAN CHARACTERIZATION USING HIGH RESOLUTION SATELLITE IMAGERY

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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    • pp.413-416
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    • 2006
  • As even small features can be classified as high resolution imagery, urban remote sensing is regarded as one of the important application fields in time of wide use of the commercialized high resolution satellite imageries. In this study, we have analyzed the variogram properties of high resolution imagery, which was obtained in urban area through the simple modeling and applied to the real image. Based on the grasped variogram characteristics, we have tried to decomposed two high-resolution imagery such as IKONOS and QuickBird reducing window size until the unique variogram that urban feature has come out and then been indexed. Modeling results will be used as the fundamental data for variographic analysis in urban area using high resolution imagery later on. Index map also can be used for determining urban complexity or land-use classification, because the index is influenced by the feature size.

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트리구조 신경망을 이용한 냉연 강판 표면 결함의 분류 (Classification of Surface Defects on Cold Rolled Strip by Tree-Structured Neural Networks)

  • 문창인;최세호;김기범;주원종
    • 대한기계학회논문집A
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    • 제31권6호
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    • pp.651-658
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    • 2007
  • A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

공간통계학적 방법에 의한 소나무 재선충 피해의 자연적 확산유형분석 (Natural Spread Pattern of Damaged Area by Pine Wilt Disease Using Geostatistical Analysis)

  • 손민호;이우균;이승호;조현국;이준학
    • 한국산림과학회지
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    • 제95권3호
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    • pp.240-249
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    • 2006
  • 최근, 소나무재선충(Bursaphelenchus xylophilus)에 의한 소나무림의 피해에 대한 사회적 심각성이 크게 대두되고 있다. 소나무 재선충에 의한 산림피해는 피해지 내에서는 매개충인 솔수염하늘소의 자연적인 영역확장에 의해 확산되는 반면, 전국적으로는 감염목의 인위적 반출 및 이동에 의해 확산이 진행되고 있다. 본 연구에서는 부산 대변항의 재선충 피해지내에서 항공사진 및 현지조사에 의해 피해목의 공간적인 위치를 파악하였고, 공간통계학적인 방법을 통하여 피해목의 공간분포유형, 피해발생과 지형인자간의 관계를 분석하였다. 또한, 지형공간자료를 통계학적 Tree 모형에 적용한 CART(Classification and Regression Trees)모형을 이용하여 재선충 피해의 자연적인 확산 예측 지도를 작성하였다. 본 연구를 통해 공간통계학적인 분석과 CART모형이 소나무재선충 피해의 공간분포 및 자연적 확산유형을 파악하는데 유용한 도구로 활용될 수 있음을 확인할 수 있었다.

석회암 공동발달유형에 따른 터널지보패턴의 표준화에 대한 연구 (Standardization of tunnel supporting system in karst formation)

  • 김상환
    • 한국터널지하공간학회 논문집
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    • 제5권3호
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    • pp.279-289
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    • 2003
  • 일반적으로 석회암 공동발달지역의 터널지보는 터널의 안정성을 좌우하는 매우 중요한 요소중에 하나이다. 이를 위하여 설계단계에서 석회암 공동발달지역과 같은 불확실성 지반조건에서 터널의 지보패턴에 대하여서는 용이하게 결정 할 수 없을 것이다. 따라서 석회암 공동발달지역에서의 일반적으로 제시할 수 있는 터널지보패턴에 대한 표준화가 요구되어진다. 이 논문은 석회암공동발달지역에서의 터널지보패턴의 표준화기법에 대한 연구 결과를 제시하였다. 이 연구는 국내의 석회암 공동발달지역의 불확실한 지반조건에서의 터널지보 System에 대한 간편화 기법에 대하여 기술하였다. 특히, 석회암공동발달지역에 대한 지반의 등급화기법 뿐만 아니라 이에 따른 터널지보패턴 간편화 기법에 대하여서도 제시하였다. 또한, 석회암 공동지반등급과 지보패턴별 요구되는 보강 및 보조공법에 대하여서도 상세 서술하였다. 이 연구를 수행하기 위하여 석회암 공동이 발달되어 있는 ${\bigcirc}{\bigcirc}$지역에 계획되었던 터널에 대하여 실질적으로 설계과정을 통하여 지보패턴의 형식선정기법의 적용에 대한 연구를 실시하였다. 이 연구 결과를 통하여 향후 석회암 공동발달지역 뿐만 아니라 이와 유사지반에서의 터널지보 설계에 적용하므로써 터널기술향상을 도모할 것이다.

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2015년~2021년 한반도 고농도 미세먼지 사례의 유형분류에 따른 기상학적 특징 분석 (Analysis of Meteorological Characteristics by Fine Dust Classification on the Korean Peninsula, 2015~2021)

  • 지준범;조창래;김유준;박승식
    • 대기
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    • 제32권2호
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    • pp.119-133
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    • 2022
  • From 2015 to 2021, high-concentration fine dust episodes with a daily average PM2.5 concentration of 50 ㎍ m-3 or higher were selected and classified into 3 types [long range transport (LRT), mixed (MIX) and Local emission and stagnant (LES)] using synoptic chart and backward trajectory analysis. And relationships between the fine particle data (PM2.5 and PM10 concentration and PM2.5/PM10 ratio) and meteorological data (PBLH, Ta, WS, U-wind, and Rainfall) were analyzed using hourly observation for the classification episodes on the Korean Peninsula and the Seoul metropolitan area (SMA). In LRT, relatively large particles such as dust are usually included, and in LES, fine particle is abundant. In the Korean peninsula, the rainfall was relatively increased centered on the middle and western coasts in MIX and LES. In the SMA, wind speed was rather strong in LRT and weak in LES. In LRT, rainfall was centered in Seoul, and in MIX and LES, rainfall appeared around Seoul. However, when the dust cases were excluded, the difference between the LRT and other types of air quality was decreased, but the meteorological variables (Ta, RH, Pa, PBLH, etc.) were further strengthened. In the case of the Korean Peninsula, it is difficult to find a clear relationship because regional influences (topographical elevation, cities and coasts, etc.) are complexly included in a rather wide area. In the SMA, it is analyzed that the effects of urbanization such as the urban heat island centered on Seoul coincide with the sea and land winds, resulting in a combination of high concentrations and meteorological phenomena.