• Title/Summary/Keyword: 대분수

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A Study on the Sample Design for the Labor Statistics - Monthly Labor Statistics Survey and Labor Demand Survey - (노동통계조사를 위한 표본설계 - 매월노동통계조사, 노동력수요동향조사를 중심으로 -)

  • 이기재;전종우
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.215-226
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    • 1997
  • The purpose of the labor statistics survey is to collect materials on employment, wages and the working time and to analyze the trend of the labor situation. in this research, the stratification variables are industry and the size of establishment. The sample are selected by stratified one stage sampling method in order to produce the reliable estimates of labor statistics. For local labor statistics, we design the sample survey using the city and province as sub-population. So we are able to produce the local area estimates of labor statistics with respect to industry and the size of establishment.

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Biological Characteristics of Microsporum canis isolated from canine dermatophytosis (개 피부병 유래의 Microsporum canis의 생물학적 성상)

  • Han, Ki-ok;Choi, Won-pil
    • Korean Journal of Veterinary Research
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    • v.41 no.2
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    • pp.167-172
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    • 2001
  • The present study was conducted to examine morphological and biological characteristics of 57 strains of Microsporum canis isolated from 110 dogs with dermatophytosis in Taegu, 1999. Isolated strains of M canis were classified into 4 types(A: white-yellow type, B: fluffy type, C: flat type, D: radial groove type) according to their pigmentation and morphology of colonies with typical conidia and hyphae. Some strains of A and B type happened variation by subculture for 6~8 months. The variation strains were classified into 3 types(E, F, G), E type had aberrant macroconidia with typical macroconidia, F type had aberrant hyphae(like dumb-bell) and macroconidia, and G type had no conidia and racket hyphae. All strains showed positive urease test, rice medium growth test and hair perforation test.

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Automatic Photograph Classification Using Geographical Information (지리정보를 이용한 자동사진분류)

  • Hong, Young-Jin;Kim, Seong-Woon;Yoo, Myung-Hyun;Lee, Yong-Beom;Kim, Sang-Ryong
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.692-698
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    • 2006
  • 점점 더 많은 디지털 카메라와 휴대폰이 고해상도 카메라가 장착되고 대용량의 저장공간이 제공되면서 사용자들의 사진촬영 빈도가 증대하고 있다. 조만간 휴대폰의 저장된 사진을 효과적으로 관리하고 브라우징할 수 있는 기술이 필요한 시기가 올 것이다. 본 논문은 휴대폰이나 디지털 카메라 혹은 카메라가 장착되어 사진을 찍을 수 있는 모든 형태의 휴대단말에서 촬영된 개인사진을 지리적 위치정보를 이용하여 자동으로 분류하는 시스템을 제시한다. 기존의 시간정보를 이용하여 촬영시간의 근접성을 이용해 순차적으로 자동 분류하는 시스템과는 달리 위치정보를 이용하여 촬영위치에 따라 비순차적으로 자동 분류한다. 촬영위치 근접성을 결정하기 위해 밀도기반 클러스터링 알고리즘을 사용하여 전체 사진을 대분류하고 기존의 자동사진 분류방식에서는 다루지 않았던 일상사진과 비일상사진을 분류하고, 대분류된 사진을 시간정보를 이용하여 소분류 함으로서 자동 사진분류 성능을 높이고자 한다.

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Multi-Level Content-Based Image Retrieval Technique Using Feature Information (특징 정보를 이용한 다단계 내용기반 영상 검색 기법)

  • 김봉기;오해석
    • Proceedings of the Korea Database Society Conference
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    • 1998.09a
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    • pp.395-405
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    • 1998
  • 최근 멀티미디어 기술의 발전으로 인해 영상을 효율적으로 검색할 수 있는 영상 데이터베이스 시스템이 정보화 사회의 중요한 핵심 기술로 대두되고 있다. 본 논문에서는 내용기반 영상 데이터 검색을 위한 영상 특징 추출 방법으로 색상 정보와 모양 정보를 고려하는 다단계 영상 검색 시스템을 제안하였다. 1단계에서는 색상 정보론 얻기 위해서는 Striker 등이 제시한 색상 분포 특성을 이용한 색인 방법의 문제점을 보완하고 확장해서 지역 색상 분포 특성을 고려한 색인 방법을 사용하여 1차로 영상을 대분류한다. 2단계에서는 1단계에서 대분류된 집단 영상들에 대하여 2차로 모양 정보를 이용하여 사용자가 질의한 영상과 유사한 영상을 최종적으로 검색한다. 모양 정보를 얻기 위해서는 기존 불변 모멘트의 문제점인 많은 연산량과, Jain 등이 제시한 방향 히스토그램 인터섹션 방법에서 제기된 회전에 민감하다는 문제점을 해결하기 위해 물체의 윤곽선에 해당하는 화소들만을 대상으로 연산을 수행하는 향상된 불변 모멘트(Improved Moment Invariants : IMI)를 이용한다. 실험 영상으로 300개의 자동차 영상을 사용하여 기존 방법들과의 비교 실험을 통해 향상된 검색 결과를 얻을 수 있었다.

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Recognition of Korean Text in Outdoor Signboard Images Using Directional Feature and Fisher Measure (방향성분 특징과 Fisher Measure를 이용한 간판영상 한글인식)

  • Lim, Jun-Sik;Kim, Soo-Hyung;Lee, Guee-Sang;Yang, Hyung-Jung;Lee, Myung-Eun
    • The KIPS Transactions:PartB
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    • v.16B no.3
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    • pp.239-246
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    • 2009
  • In this paper, we propose a Korean character recognition method from outboard signboard images. We have chosen 808 classes of Korean characters by an analysis of frequencies of appearance in a dictionary of signboard names. The proposed method mainly consists of three steps: feature extraction, rough classification, and coarse classification. The first step is to extract a nonlinear directional segments feature, which is immune to the distortion of character shapes. The second step computes an ordered set of 10 recognition candidates using a minimum distance classifier. The last step reorders the recognition candidates using a Fisher discriminant measure. As experimental results, the recognition accuracy is 80.45% for the first choice, and 93.51% for the top five choices.

A Study on the Quotient and Remainder in Division of Decimal (소수 나눗셈에서 몫과 나머지에 관한 소고)

  • Jeong, Sangtae
    • Education of Primary School Mathematics
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    • v.19 no.3
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    • pp.193-210
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    • 2016
  • In the $10{\div}2.4$ problem situation, we could find that curious upper and middle level students' solution. They solved $10{\div}2.4$ and wrote the result as quotient 4, remainder 4. In this curious response, we researched how students realize quotient and remainder in division of decimal. As a result, many students make errors in division of decimal especially in remainder. From these response, we constructed fraction based teaching method about division of decimal. This method provides new aspects about quotient and remainder in division of decimal, so we can compare each aspects' strong points and weak points.

Fast Handwriting Recognition Using Model Graph (모델 그래프를 이용한 빠른 필기 인식 방법)

  • Oh, Se-Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.5
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    • pp.892-898
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    • 2012
  • Rough classification methods are used to improving the recognition speed in many character recognition problems. In this case, some irreversible result can occur by an error in rough classification. Methods for duplicating each model in several classes are used in order to reduce this risk. But the errors by rough classfication can not be completely ruled out by these methods. In this paper, an recognition method is proposed to increase speed that matches models selectively without any increase in error. This method constructs a model graph using similarity between models. Then a search process begins from a particular point in the model graph. In this process, matching of unnecessary models are reduced that are not similar to the input pattern. In this paper, the proposed method is applied to the recognition problem of handwriting numbers and upper/lower cases of English alphabets. In the experiments, the proposed method was compared with the basic method that matches all models with input pattern. As a result, the same recognition rate, which has shown as the basic method, was obtained by controlling the out-degree of the model graph and the number of maintaining candidates during the search process thereby being increased the recognition speed to 2.45 times.

Using collaborative filtering techniques Mobile ad recommendation system (협업필터링 기법을 이용한 모바일 광고 추천 시스템)

  • Kim, Eun-suk;Yoon, Sung-dae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.3-6
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    • 2012
  • Due to recent rapid growth of mobile market, the modern people increasing make use of mobile contents as a means to obtain the desired information quickly by overcoming various restraints of a computer. The wide range of recommended contents, however, takes much time in selection of contents. To resolve such issues, a system that predicts the contents desired by the user and makes an accurate recommendation is necessary. In this paper, in order to provide the desired contents in line with the user demands, a method to increase select the number of recommendation using cooperative filtering is proposed. In the first step, the categories are formulated with super-classes and the similarity between the target customer and users is found, and the nearest-neighbors are constituted to find the preference predictions between super-classes, and the super-class with the highest resulting value is recommended to the target customer. In the second step, the preference predictions between sub-classes are found and the sub-class with the highest value is recommended to the target customer. In the experiment, mobile contents are recommended through super-class-based cooperative filtering, and then the mobile contents are recommended through sub-class-based cooperative filtering, and sub-class collaborative filtering method to select a high number of verification.

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The Relative Importance and Priority of the Health Evaluation Indicators of Old-growth and Giant Trees (노거수의 건강 위험도 평가 요소간 상대적 중요도 및 우선순위)

  • Xia, Tian-Tian;Zhang, Zhong-Feng;Kang, Tai-Ho
    • Journal of the Korean Institute of Landscape Architecture
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    • v.45 no.6
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    • pp.149-159
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    • 2017
  • There are many studies on the health and protection of Old-growth and Giant Trees, concentrating on empirical judgment and basic protection measures. The problem this study addresses is the relative importance and priority of the health evaluation indicators of Old-growth and Giant Trees. Firstly, this study exports the evaluation indicators of Old-growth and Giant Trees. The evaluation system for the degree of danger of Old-growth and Giant Trees are composed of two layers: 5 fields and 46 indicators. Secondly, using the AHP and PCA method can determine the weight of each field and each index factor. The process of AHP establishes the relative importance judgment matrix of each field and fully proves that the main cause of danger is individual aging. The PCA method suggested that trunk rot status, light conditions, tree surgeries, bacterial diseases, and soil moisture level are the most important factors in each field. These aspects should be given priority in the management and protection of Old-growth and Giant Trees. Weight values obtained in this study seemed to be useful in the evaluation of Old-growth and Giant Trees.

Reconstruction of Categories on the National Petition Site Using K-Means clustering and Topic Modeling (K-means 클러스터링과 토픽 모델링을 기반으로 한 국민청원 사이트의 카테고리 재구성)

  • Woo, Yun Hui;Kim, Hyon Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.302-305
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    • 2019
  • 국민 청원 사이트가 뛰어난 접근성과 신속성으로 인하여 국민들로부터 많은 관심을 받고 있다. 현재 국민청원 사이트의 카테고리 분류는 '미래', '성장동력' 등을 포함한 16개의 카테고리 및 기타로 구성되어 있으나 그 기준이 모호하여 많은 청원글들이 기타 카테고리로 분류되고 있는 상황이다. 이는 청원글의 내용을 명확히 반영하지 않고 미리 정의된 카테고리 구조를 사용하고 있는데서 기인한다고 할 수 있다. 본 논문에서는 보다 구체적으로 정의된 카테고리를 정의하고자 추천 순으로 1,500개의 청원글을 수집하였고, 수집된 청원글의 내용을 바탕으로 카테고리 구조를 추출하였다. 먼저, k-평균 알고리즘을 적용하여 청원글을 군집하여 대분류를 정의하였고, 보다 구체적인 세부 분류를 정의하기 위하여 토픽모델링을 실시하였다. 본 논문에서 제시하는 계층적 카테고리 구조는 청원글의 내용을 바탕으로 대분류와 세부분류로 구성된 것이므로 새로운 청원글을 등록하거나 분류하는 데 적절한 것으로 보인다.