• 제목/요약/키워드: CLASSIFICATION INDICATOR

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퍼지 클래스 벡터를 이용하는 다중센서 융합에 의한 무감독 영상분류 (Unsupervised Image Classification through Multisensor Fusion using Fuzzy Class Vector)

  • 이상훈
    • 대한원격탐사학회지
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    • 제19권4호
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    • pp.329-339
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    • 2003
  • 본 연구에서는 무감독 영상분류를 위하여 특성이 다른 센서로 수집된 영상들에 대한 의사결정 수준의 영상 융합기법을 제안하였다. 제안된 기법은 공간 확장 분할에 근거한 무감독 계층군집 영상분류기법을 개개의 센서에서 수집된 영상에 독립적으로 적용한 후 그 결과로 생성되는 분할지역의 퍼지 클래스 벡터(fuzzy class vector)를 이용하여 각 센서의 분류 결과를 융합한다. 퍼지 클래스벡터는 분할지역이 각 클래스에 속할 확률을 표시하는 지시(indicator) 벡터로 간주되며 기대 최대화 (EM: Expected Maximization) 추정 법에 의해 관련 변수의 최대 우도 추정치가 반복적으로 계산되어진다. 본 연구에서는 같은 특성의 센서 혹은 밴드 별로 분할과 분류를 수행한 후 분할지역의 분류결과를 퍼지 클래스 벡터를 이용하여 합성하는 접근법을 사용하고 있으므로 일반적으로 다중센서의 영상의 분류기법에 사용하는 화소수준의 영상융합기법에서처럼 서로 다른 센서로부터 수집된 영상의 화소간의 공간적 일치에 대한 높은 정확도를 요구하지 않는다. 본 연구는 한반도 전라북도 북서지역에서 관측된 다중분광 SPOT 영상자료와 AIRSAR 영상자료에 적용한 결과 제안된 영상 융합기법에 의한 피복 분류는 확장 벡터의 접근법에 의한 영상 융합보다 서로 다른 센서로부터 얻어지는 정보를 더욱 적합하게 융합한다는 것을 보여주고 있다.

A study of bioindicator selection for long-term ecological monitoring

  • Han, Yong-Gu;Kwon, Ohseok;Cho, Youngho
    • Journal of Ecology and Environment
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    • 제38권1호
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    • pp.119-122
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    • 2015
  • It is very useful and important to see the status and change of necessary parts in a short period through selecting and observing the bioindicator continually to forecast and prepare the future. Especially, living things are so closely related to the environment that the indicator between the environment and living things shows close interrelationship. Also, the indicator related to environment provides information about representative or decisive environmental phenomenon and is used to simplify complicated facts. Considering wide range of background and application including various indicators such as the change-, destruction-, pollution-, and restoration of habitats, climate change, and species diversity, the closest category includes "environmental indicator," "ecological indicator," and "biodiversity indicator." The selection and use of bioindicator is complicated and difficult. The necessary conditions for the indicator selection are flexible and greatly depend on the goals of investigation such as the indicator for biological diversity investigation of specific area, the indicator for habitat destruction, the indicator for climate change, and the indicator for polluted area. It should meet many various conditions to select a good indicator. In this study, eleven selection standards are established based on domestic and overseas studies on bioindicator selection: species with clear classification and ecology, species distributed in geographically widespread area, species that show clear habitat characteristics, species that can provide early warning for a change, species that are easy and economically benefited for the investigation, species that have many independent individual groups and that is not greatly affected by the size of individual groups, species that is thought to represent the response of other species, species that represent the ecology change caused by the pressure of human influence, species for which researches on climate change have been done, species that is easy to observe, appears for a long time and forms a group with many individuals, and species that are important socially, economically, and culturally.

이분적 터널 암반 분류를 위한 정성적 자료의 지구 통계학적 연구 -1. 이론 (A Geostatistical Study Using Qualitative Information for Tunnel Rock Binary Classification 1. Theory)

  • 유광호
    • 한국지반공학회지:지반
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    • 제9권3호
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    • pp.61-66
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    • 1993
  • 본 논문에서는 암반 분류를 위해 물리탐사 결과나 그동안 축적된 시공경험 등의 정성적 자료의 사용을 고려하였다. 터널 설계를 위한 요소(parameter)들이 공간적 상관관계를 갖기 때문에 지구 통계학(Geostatistics)을 이용하였으며, 특히, 비모수적 (non-parametric)방법 중의 하나인 지시 크리깅(indicator kriging) 기법을 사용했다. 최적 분류를 위한 선택 기준으로는 오차에 대응하는 비용(the cost of errors)을 사용했으며, 암반분류는 이분적 분류에 한정하였다. 앞으로, 정량적 데이타가 절대적으로 부족한 터널공사등에서 비교적 많은 양이 존재하는 정성적 데이타의 이용은 절실하며, 이러한 점에서 본 연구가 가지는 의미는 크다.

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한의대생의 성별에 따른 MBTI와 MMPI-2 특성 연구 (A Study on Myers-Briggs Type Indicator and Minnesota Multiphasic Personality Inventory-2 Characteristics Based on Gender of Oriental Medicine Students)

  • 이재혁
    • 동의신경정신과학회지
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    • 제28권4호
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    • pp.373-379
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    • 2017
  • Objectives: The purpose of this research is to study the psychological characteristics of Korean medical students with a focus on the Myers-Briggs Type Indicator (MBTI) and the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Methods: The survey was conducted on 101 Korean medical students to investigate their psychological characteristics with a focus on Myers-Briggs Type Indicator and the Minnesota Multiphasic Personality Inventory-2. Results: Among the 16 MBTI personality types, ISTJ was the most common type with the prevalence of 24.8%. According to gender-based classification, there were more men in the J-type category and more women in the P-type category. In the MMPI-2 scales, males showed high scores in Pd, AGGR, DISC, MAC-R, and GM, and females showed high scores in Mf and GF. Conclusions: The personality test for male and female Korean medical students revealed few differences on some scales of the Myers-Briggs Type Indicator and the Minnesota Multiphasic Personality Inventory-2.

Analysis of the Relation between Biological Classification Ability and Cortisol-hormonal Change of Middle School Students

  • Bae, Ye-Jun;Lee, Il-Sun;Byeon, Jung-Ho;Kwon, Yong-Ju
    • 한국과학교육학회지
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    • 제32권6호
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    • pp.1063-1071
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    • 2012
  • The purpose of this study is to investigate the relation between the classification ability quotient and cortisol-hormonal change of middle school students. Thirty-three students, second graders in middle school, performed the classification task that can be an indicator of students' classification ability. And then amount of the secreted hormone was analyzed during task performance. The study results were as follows: First, the classification methods of students mostly utilized visual, qualitative. Their classification patterns for each subject were static, partial, and non-comparative. Second, the amount of stress-hormone was secreted from students during the experiment decreased in overall after the free classification. It seemed that student-centered activity relieved stress. Third, the classification ability quotient turned out to be significantly correlated to the stress hormone, which means that there was a close relationship between classification ability and stress level. It was also considered that stress had a positive effect on the improvement of classification ability. This study provided physiologically more accurate information on the stress increased in the learning process than other conventional studies based on reports or interviews. Finally, researchers could recognize the effect of stress in the cognitive activity and the need to find an appropriate level of stress in learning processes.

Development and testing of a composite system for bridge health monitoring utilising computer vision and deep learning

  • Lydon, Darragh;Taylor, S.E.;Lydon, Myra;Martinez del Rincon, Jesus;Hester, David
    • Smart Structures and Systems
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    • 제24권6호
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    • pp.723-732
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    • 2019
  • Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

Geostatistical Fusion of Spectral and Spatial Information in Remote Sensing Data Classification

  • Park, No-Wook;Chi, Kwang-Hoon;Kwon, Byung-Doo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.399-401
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    • 2003
  • This paper presents a geostatistical contextual classifier for the classification of remote sensing data. To obtain accurate spatial/contextual information, a simple indicator kriging algorithm with local means that allows one to estimate the probability of occurrence of certain classes on the basis of surrounding pixel information is applied. To illustrate the proposed scheme, supervised classification of multi-sensor remote sensing data is carried out. Analysis of the results indicates that the proposed method improved the classification accuracy, compared to the method based on the spectral information only.

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초등학교 공간계획을 위한 지역유형분류 및 특성분석 -서울·경기 지역을 중심으로- (A Study on Community Classification and Property Analysis for Space Planning of Elementary School -Focusing on the Seoul and Gyeonggi Province-)

  • 이상민
    • 교육녹색환경연구
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    • 제3권2호
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    • pp.21-37
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    • 2003
  • This study has the purpose for analysis of each region's property in order to plan a elementary school's space according to community property. For this analysis. we used classification method through classification analysis. classification analysis is one of the useful statistical analysis methode for determining each region's policy through classifying regions which have a similar property. On this study, Seoul and Kyongkido is classified by 4 groups and each group has a different community property. Such a analysis is thought of helping establishing the objective. reasonable space-plan through comparative analysis between subjective claim and objective state indicator of each region.

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기술 경쟁력 평가를 위한 정성적 산업기술 수준지표 개발 (Development of the Qualitative Industrial Technological Level Indicator to Evaluate the Technology Competitiveness)

  • 이재하;박상민
    • 산업경영시스템학회지
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    • 제20권42호
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    • pp.67-72
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    • 1997
  • How to measure technological level has concerned research analysists for a long time. Many methods exist, and they all have their advantages and disadvantages according to how they are used. The purpose of this study is to develop qualitative indicator to measure industrial technological level, in particular manufacturing capacity. In this indicator, the two basis of technology classification and the concept of the technology competitiveness were introduced. First, the types of technology are classified as three classes : material technology, processing technology and product technology. Second, the characteristics of technology are divided into the three categories : core technology, peripheral technology and sprouting technology On this basis, the qualitative technological level was made in terms of the competitiveness of it's manufacturing capacity. This study should be a practical approach for application of measuring of technological level.

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지역보건 관련 소지역간 건강증진지표 개발에 관한 연구 (Development of Small Area Health Promotion Indicator for Community Health Initiative)

  • 김춘배;고광욱;박재성;최헌
    • 보건교육건강증진학회지
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    • 제20권1호
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    • pp.19-39
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    • 2003
  • Purpose: Although there is a lot of secondary data available for comparing community health status and planning health policies in terms of large area such as metropolitan cities or provinces, there is restricted data for establishing community health policies of the small areas such as towns, Gun(i.e., districts), and Gu. Specifically, the problems of producing a valuable index for health promotion in small areas are three fold: First, there is not an appropriate index model for measuring a small community health status. Second, a large part of secondary data in the small areas has been produced in an irregular time interval. In addition, all valuable data can not be integrated without time consuming work. Thus this study tries to establish a health promotion index model for assisting community health promotion initiatives of local governments. Methods and materials: Literature review, community health specialist consultation and a questionnaire survey was performed. Results: Based on Dever's model, a prototype of health promotion indicators was proposed and modified by the community health specialists. 15 classification scheme of statistical yearbook reorganized into the six areas. Those six areas were comprised in 24 indicator class with 96 specific indicators. Through further modification processes by a questionnaire survey, we developed a health promotion indicator model that contains six areas with 23 indicator class encompassed by 87 specific indicators. Conclusions: This study proposed a model of health promotion indicator comprised in the six areas with 23 indicator classes for measuring small area health promotion status. However, more specific or additional data in human biology, environment, and socioeconomic data is essential for producing a stronger model for health promotion measurement.