• Ocean and Polar Research
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• 제29권1호
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• pp.69-80
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• 2007

This paper attempts to measure the environmental value of the Nakdong-river estuary, which is ecologically important but confronted with the threat of development. Especially, in order to elicit the environmental values of its four attributes, contingent valuation method(CVM) based on multi-attribute utility theory is applied and the CVM survey was rigorously designed to comply with the guidelines for best-practiced CVM studies. We surveyed a randomly selected sample of 400 and 350 households in Busan and six large cities(Seoul, Incheon, Daegu, Daejeon, Gwangju, and Ulsan), respectively and asked respondents questions in person-to-person interviews about how they would willing to pay for the estuary conservation and management program. Respondents overall accepted the contingent market and were willing to contribute a significant amount(2,457 won in Busan and 3,560 won in six large cities), on average, per household per year, which implies that there exists a large difference between the two. The aggregate values of the Nakdong-river estuary in Busan and six large cities amount to 2.92 and 22.32 billion won, respectively, per year. In addition, expanding the values to Korea produces 51.34 billion won per year. The quantitative values can be utilized in planning and decision-making about development versus conservation of the estuary.

• 한국지능시스템학회논문지
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• 제10권3호
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• pp.232-241
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• 2000

본 연구는 대량의 데이터에서 효율적으로 최적 규칙을 발견하기 위해 개념 계층과 정보 이득 및 라프셋 이론에 딕반한 통합 방법을 제시하고,이를 최적 규칙 발견 시스템으로 구현한다. 본 방법은 데이터베이스에 있는 데이터에서 일반화된 지식을 추출하기 위한 속성중심의 개념 상승 기법과 불필요한 속성 및 속성값을 제거하기 위한 지식 감축 기법을 적용하며, 최적 규칙의 도출을 위해 속성의 중요도를 사용한다. 본 시스템은 먼저, 속성값 개념의 일반화에 의해 종복 튜플을 제거함으로써 데이터 베이스의 크기를 줄이고, 결정속성에 뎡향을 주지않는 조건속성을 제거하여 간략화된 최적 규칙을 유도한다.그리고 실제 데이터에 적용하여 결정 규칙을 유도하고 그 규칙을 새로운 데이터에 테스트햐 봄으로써 새로운 데이터에도 잘 적용됨을 보인다.

• 한국지능시스템학회논문지
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• 제19권2호
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• pp.265-272
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• 2009

Fuzzy number intuitionistic fuzzy sets (FNIFSs), each of which is characterized by a membership function and a non-membership function whose values are trigonometric fuzzy number rather than exact numbers, are a very useful means to describe the decision information in the process of decision making. Wang [10] developed some arithmetic aggregation operators, such as the fuzzy number intuitionistic fuzzy weighted averaging (FIFWA) operator, the fuzzy number intuitionistic fuzzy ordered weighted averaging (FIFOWA) operator and the fuzzy number intuitionistic fuzzy hybrid aggregation (FIFHA) operator. In this paper, based on the FIFHA operator and the FIFWA operator, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as fuzzy number intuitionistic fuzzy decision matrices where each of the elements is characterized by fuzzy number intuitionistic fuzzy numbers, and the information about attribute weights is partially known. An example is used to illustrate the applicability of the proposed approach.

• 정보관리학회지
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• 제40권4호
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• pp.279-306
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• 2023

본 연구는 다양한 관점의 이용요구가 혼재되어있는 독서자료의 속성을 파악하기 위해, 도서의 동시이용 (동시대출, 동시구매) 데이터에 기반하여 독서자료의 선택 및 이용과 관계된 서지적 속성을 분석하였다. KDC 주제, 독자대상, 이용자 연령 관련 26개 하위 속성 단위로 구분하여 서지적 속성 용어의 동시출현행렬을 생성하고 네트워크 분석을 수행한 결과, 독서자료의 서지적 속성의 세부 내용 및 두드러진 매개 역할을 파악하였다. 본 연구의 결과는 향후 도서관 OPAC을 비롯한 독서정보 시스템의 패싯 설계에 도움이 될 것이다.

• 융합정보논문지
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• 제9권5호
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• pp.7-13
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• 2019

클라우드 환경이나 빅데이터 환경에서의 역할기반 또는 속성기반의 접근제어에는 계층적 모델을 표현하는 적당한 수학적 구조가 필요하다. 본 논문에서는 역할기반 또는 속성기반의 접근제어의 계층적 모델을 구현할 수 있는 격자함의 대수에서 멀티플라이어와 단순 멀티플라이어의 개념을 정의하고, 모든 멀티플라이어는 단순 멀티플라이어임을 증명한다. 또한 격자함의대수 L의 멀티플라이어와 준동형사상의 관계를 조사하고, 각각의 $u{\in}L$에 대하여 격자 [0, u]와 격자 $[u^{\prime},1]$이 동치임과 $u{\vee}u^{\prime}=1$인 $u{\in}L$에 대하여 L과 $[u,1]{\times}[u^{\prime},1]$이 격자함의대수로써 동치임을 보인다.

• 한국정보시스템학회지:정보시스템연구
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• 제8권2호
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• 디지털산업정보학회논문지
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• 제16권1호
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• 산업경영시스템학회지
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• 제28권1호
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• pp.1-7
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• 2005

Data mining is widely used for turning huge amounts of data into useful information and knowledge in the information industry in recent years. When analyzing data set with continuous values in order to gain knowledge utilizing data mining, we often undergo a process called discretization, which divides the attribute's value into intervals. Such intervals from new values for the attribute allow to reduce the size of the data set. In addition, discretization based on rough set theory has the advantage of being easily applied. In this paper, we suggest a discretization algorithm based on Rough Set theory and SOM(Self-Organizing Map) as a means of extracting valuable information from large data set, which can be employed even in the case where there lacks of professional knowledge for the field.

• 한국정보과학회논문지:데이타베이스
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• 제28권4호
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• pp.596-605
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• 2001

본 논문은 OLAP에서의 I/O 비용을 줄이는 큐브 계산 방법으로, 구간 기반 큐브 분할 기법을 제안한다. 제안하는 방법은 큐브 분할 단계들 사이에 존재하는 계산의 일부를 중복시켜 처리하는 방법을 통해 큐브 분할 작업의 I/O 성능을 향상시킨다. 계산의 중복을 위하여 제안하는 방법은 애트리뷰트의 단 일 값이 아닌 애트리뷰트 값의 일정 구간을 기준으로 큐브를 분할한다 분석과 실험을 통하여 제안하는 방법의 성능을 기존 큐브 분할 방법과 비교하여 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3401-3420
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• 2021

We provide a traceable ciphertext-policy attribute based encryption (CP-ABE) construction for monotone access structures (MAS) based on composite order bilinear groups, which is secure adaptively under the standard model. We construct this scheme by making use of an "encoding technique" which represents the MAS by their minimal sets to encrypt the messages. To date, for all traceable CP-ABE schemes, their encryption costs grow linearly with the MAS size, the decryption costs grow linearly with the qualified rows in the span programs. However, in our traceable CP-ABE, the ciphertext is linear with the minimal sets, and decryption needs merely three bilinear pairing computations and two exponent computations, which improves the efficiency extremely and has constant decryption. At last, the detailed security and traceability proof is given.