• 제목/요약/키워드: Classification of Information System

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Feature Impact Evaluation Based Pattern Classification System

  • Rhee, Hyun-Sook
    • 한국컴퓨터정보학회논문지
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    • 제23권11호
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    • pp.25-30
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    • 2018
  • Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

데이터베이스 기술 분류 표준화 연구 (A Study on the Standardization for the Classification of Database Technologies)

  • 최명규
    • 정보관리연구
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    • 제27권2호
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    • pp.33-64
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    • 1996
  • 본 연구는 데이터베이스 기술분류의 표준시안을 제시하기 위하여 1차년도(1994년) 연구 결과에 대한 관점을 체계화하고 구체화시켜 수정, 보완하는 형식으로 이루어졌다. 분류관점을 정보와 이를 지원하는 시스템 측면으로 크게 나누어, 데이터베이스 일반, 정보유통, 정보검색, 데이터베이스 시스템, 주변 관련주제를 분류기준으로 하는 표준 시안의 모형이 제시되었다.

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Web-based synthetic-aperture radar data management system and land cover classification

  • Dalwon Jang;Jaewon Lee;Jong-Seol Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권7호
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    • pp.1858-1872
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    • 2023
  • With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.

중소기업용 스마트팩토리 보안 취약점 분류체계 개발: 산업제어시스템 중심으로 (Developing a Classification of Vulnerabilities for Smart Factory in SMEs: Focused on Industrial Control Systems)

  • 정재훈;김태성
    • 한국IT서비스학회지
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    • 제21권5호
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    • pp.65-79
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    • 2022
  • The smart factory has spread to small and mid-size enterprises (SMEs) under the leadership of the government. Smart factory consists of a work area, an operation management area, and an industrial control system (ICS) area. However, each site is combined with the IT system for reasons such as the convenience of work. As a result, various breaches could occur due to the weakness of the IT system. This study seeks to discover the items and vulnerabilities that SMEs who have difficulties in information security due to technology limitations, human resources, and budget should first diagnose and check. First, to compare the existing domestic and foreign smart factory vulnerability classification systems and improve the current classification system, the latest smart factory vulnerability information is collected from NVD, CISA, and OWASP. Then, significant keywords are extracted from pre-processing, co-occurrence network analysis is performed, and the relationship between each keyword and vulnerability is discovered. Finally, the improvement points of the classification system are derived by mapping it to the existing classification system. Therefore, configuration and maintenance, communication and network, and software development were the items to be diagnosed and checked first, and vulnerabilities were denial of service (DoS), lack of integrity checking for communications, inadequate authentication, privileges, and access control in software in descending order of importance.

통합건설정보분류체계의 구축방안에 관한 연구 (A Study on the Establishment Plan of Integrated Construction Information Classification)

  • 이교선;박환표;오은호;박상훈
    • 한국건설관리학회논문집
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    • 제3권2호
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    • pp.99-106
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    • 2002
  • 국내의 통일된 정보분류체계 부재는 건설분야 정보화사업의 중복투자 및 건설정보의 사장 등 인적, 물적 손실과 한께 국가 경쟁력 향상에 장애요인을 초래하고 있다. 따라서 정부 또는 민간은 정보유통의 기반조성과 정보화사업의 중복투자 방지 및 정보의 공동이용을 위한 통일된 건설정보 분류체계의 표준화사업을 조속히 추진하여, 건설CALS, 건설사업관리, 설계 $\cdot$시공 통합정보시스템, EVMS(Earned Value Management System) 등 업무의 기반을 구축할 필요가 있다. 따라서, 본 고에서는 국내 실정에 맞는 건설정보 분류체계의 발전방향을 제시하고, 정보분류체계의 활용 및 실무 적용방안을 제시하고자 한다.

물질안전보건자료 대상물질의 유해성 분류기준 적용 연구 (Study on applying to Hazard Classification Criteria of Chemicals subject to Material Safety Data Sheets)

  • 이혜진;이나루;이인섭
    • 한국산업보건학회지
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    • 제30권3호
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    • pp.280-291
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    • 2020
  • Objectives: Hazard classification is a controversial issue in the new MSDS system in which chemical companies have to prepare and submit MSDS for chemicals that they manufacture or import to the competent authorities according to the amended Occupational Safety and Health Act. The aim of this study is to suggest how to apply and manage harmonized hazard classification criteria and results by investigating current hazard classification systems and trends. Methods: The domestic issues about different hazard classification criteria and results were investigated by reviewing the literature and business outcomes regarding KOSHA. We also checked official and unofficial reports from the UN to understand international discussion about the topic. Chemical hazard classification results from agencies providing chemical information were analyzed to compare a harmonized rate between classifications. Furthermore, a field survey of a few chemical companies was conducted. Results: Under the related competent authorities, an integrated standard proposal was developed to harmonize the domestic hazard classification criteria. Although harmonized chemical information is strongly needed, we recognized the uncertainty and difficulty of harmonized hazard classification from the UN global list project review. In practice the harmonization rate of the classification was generally low between the classification in KOSHA, MoE, and EU CLP. Among hazard classes, health hazards largely led the disharmony. The field survey revealed a change of perception that the main body of chemical information production is manufacturers. Approaches and solutions about hazard classification issues differed depending on business size, types of chemical handling, and other factors. Conclusions: We proposed reasonable ways by time and step to apply hazard classification in the new MSDS system. Chemical manufacturers should make and offer chemical information including responsible hazard classifications. The government should primarily accept these classifications, evaluate them by priority, and support or supervise workplaces in order to communicate reliable chemical information.

문자 기반 유해사이트 판별 기법 (A Harmful Site Judgement Technique based on Text)

  • 정규철;이진관;이태헌;박기홍
    • 컴퓨터교육학회논문지
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    • 제7권5호
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    • pp.83-91
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    • 2004
  • 본 논문에서 청소년들의 정신 건강을 해치는 유해 정보 사이트를 차단하기 위해 기존 방식이 아닌 내용 기반을 중심으로 하여 중요도가 가장 높은 한 개의 복합 키워드와 정보통신윤리 위원회에서 제시한 유해단어의 가중치를 이용하여 가중치 평균을 더해 유해도를 판단하여 유해 사이트와 일반 사이트를 구별하는 시스템을 구현하였다. 예비 실험을 통해 구해진 유해도의 값 3.5를 유해정보 사이트를 판단하는 기준으로 정한 다음 유해 정보 차단 시스템의 성능 실험을 위해 유해 정보 사이트와 일반 사이트를 각각 무작위로 100개씩 추출해 접속해 본 결과 유해 사이트를 유해 정보 사이트로 판명한 비율이 78%를 보였고 일반 사이트를 일반 사이트로 판명한 비율이 96%가 되어 본 시스템의 유효성을 확인 할 수가 있었다.

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Automatic Payload Signature Update System for the Classification of Dynamically Changing Internet Applications

  • Shim, Kyu-Seok;Goo, Young-Hoon;Lee, Dongcheul;Kim, Myung-Sup
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권3호
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    • pp.1284-1297
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    • 2019
  • The network environment is presently becoming very increased. Accordingly, the study of traffic classification for network management is becoming difficult. Automatic signature extraction system is a hot topic in the field of traffic classification research. However, existing automatic payload signature generation systems suffer problems such as semi-automatic system, generating of disposable signatures, generating of false-positive signatures and signatures are not kept up to date. Therefore, we provide a fully automatic signature update system that automatically performs all the processes, such as traffic collection, signature generation, signature management and signature verification. The step of traffic collection automatically collects ground-truth traffic through the traffic measurement agent (TMA) and traffic management server (TMS). The step of signature management removes unnecessary signatures. The step of signature generation generates new signatures. Finally, the step of signature verification removes the false-positive signatures. The proposed system can solve the problems of existing systems. The result of this system to a campus network showed that, in the case of four applications, high recall values and low false-positive rates can be maintained.

인터넷 서점의 사회과학분야 분류체계에 관한 연구 (A Study on the Classification System for Social Science Field in Internet Bookstore)

  • 민혜영;이성숙
    • 정보관리연구
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    • 제43권1호
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    • pp.41-62
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    • 2012
  • 전자상거래의 발달로 출판유통시장에서의 인터넷 서점의 비중은 해마다 높아지고 있다. 전자책의 보급에 따라 인터넷 서점에서의 도서검색은 앞으로 더욱 활발해질 것이며, 인터넷 서점의 도서 분류체계의 중요성 또한 지속적으로 높아질 것으로 예상된다. 이 연구는 인터넷 서점 사회과학 도서의 효율적인 검색을 제공하기 위한 목적에서 이루어졌으며, 국내 외 10개 인터넷 서점의 분류체계를 분석하였다. 또한 사회과학 도서 분류체계 설계안을 구성하여 향후 사회과학 도서의 분류체계 설계에 활용될 수 있는 기초자료를 제시하고자 하였다.

Hybrid Case-based Reasoning and Genetic Algorithms Approach for Customer Classification

  • Kim Kyoung-jae;Ahn Hyunchul
    • Journal of information and communication convergence engineering
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    • 제3권4호
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    • pp.209-212
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    • 2005
  • This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.