• 제목/요약/키워드: Engineering Framework

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대규모 지진해일로 인한 침수 및 배수 시스템 프레임워크에 대한 연구 (Flooding and recovery system framework for Tsunami)

  • Lee, Sun Kee
    • 시스템엔지니어링학술지
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    • 제8권2호
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    • pp.47-55
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    • 2012
  • Tsunami disaster, which ruined Japan Fukushima nuclear power plant sites in 2011 March, has raised not only the perception of that Tsunami and/or large scale flooding possibly surpass the design baselines for industry facilities and plants, but also the necessity to establish recovery system against flooding. This study suggests the framework for flooding and drainage system in compliance with flooding and drainage concept to define and identify requirements, functions, and components of the system with traceable relations. The framework with combination to CMMI engineering process is the base of corresponding high level system design.

과학·공학 융합 수업 준거틀 및 공학 설계 수준 제안 (Suggesting a Framework for Science and Engineering Integrated Lesson Design and Engineering Design Level)

  • 남윤경;이용섭;김순식
    • 대한지구과학교육학회지
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    • 제13권1호
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    • pp.121-133
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    • 2020
  • 본 연구는 융합(STEM)교육의 핵심인 공학 설계를 기반으로 과학 수업에서 공학을 의미있고 쉽게 융함하여 수업을 설계할 수 있도록 수업 준거틀을 제안 한 것이다. 본 연구에서 개발된 과학·공학 융합 수업 준거틀은 과학과 공학 융합 교육에 대한 국내외 이론적, 실제적 선행 연구 분석과 전문가 토의, 그리고 현장교사들의 피드백에 근거하여 개발되었다. 과학·공학 융합 수업 준거틀은 과학 수업에서 공학 설계를 주요 교수법 및 문제해결 방법으로 사용하며, 선행 연구에서 제시된 공학 융합 수업의 핵심요소와 학년군별 성취수준을 고려하여 공학 설계에 대한 이해가 부족한 현장 교사들이 쉽게 공학 설계를 과학 수업에 도입할 수 있는 방법을 제공한다. 또한 본 연구에서 개발된 과학·공학 융합 수업 준거틀은 복잡하게 제시된 한국 STEAM 교육 준거틀의 단점을 보완하여 현장교사뿐 아니라 예비교사들이 쉽게 공학적 설계와 문제해결과정에 대해 이해하고 이를 적용하여 과학 융합 수업을 설계하는데 구체적인 지침을 제공할 수 있다.

PLM 지원을 위한 온톨로지 기반 지식 프레임워크 (Ontology-Based Knowledge Framework for Product Life cycle Management)

  • 이재현;서효원
    • 한국정밀공학회지
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    • 제23권3호
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    • pp.22-31
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    • 2006
  • This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

Study of Social Network Site Interactivity to Identify and Avert Usability Flaws for Effective User's Experience

  • Abduljalil, Sami;Hwang, Gi-Hyun;Kang, Dae-Ki
    • Journal of information and communication convergence engineering
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    • 제9권3호
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    • pp.325-330
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    • 2011
  • Due to the wide growth and popularity of social network website, large numbers of users discover these social network sites are a place where they can be able to spend their leisure time sharing interests, sharing ideas freely, sharing personal experience, and also to search for new friends or partners. These websites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents, which traditionally replace the common traditional methods. These social network websites need accurate and careful investigations and findings on the usability issues for effective interactivity and more usability. However, little research might have previously invested on the usability of these social network websites. Therefore, we propose a new framework to study and test the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable developers to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network websites. Performance of the framework will be performed using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

도메인 조합 기반 단백질-단백질 상호작용 확률 예측기법 (A Domain Combination Based Probabilistic Framework for Protein-Protein Interaction Prediction)

  • Han, Dong-Soo;Seo, Jung-Min;Kim, Hong-Soog;Jang, Woo-Hyuk
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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    • pp.7-16
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    • 2003
  • In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance pro-bability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated fur the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as foaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

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