• 한국농공학회논문집
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• 제50권6호
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• pp.3-12
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• 2008

It is important to estimate accurate effective rainfall to analyse flood flow and long-term runoff for the rational planning, design, and management of water resource. The initial abstraction is also important to estimate effective rainfall. The Soil Conservation Service (SCS) has developed a procedure and it has been most commonly applied to estimate effective rainfall. But the SCS method still has weak points, because of unnatural assumptions such as antecedent moisture conditions and initial abstraction. The coefficient of initial abstraction(K) is depending on the soil moisture condition and antecedent rainfall. The maximum storage capacity of Umax which is calibrated by stream flow data in the proposed watershed was derived from the DAWAST(DAily WAtershed STreamflow) model. The values of K obtained from 69 storm events at the five watersheds are ranging from 0.133 to 0.365 and its mean value is 0.207. Effective rainfall could be estimated more reasonably by introducing new concept of initial abstraction. The equation of $K=0.076Sa^{0.255}$ was recommended instead of 0.2 and it could be applicable to the small-medium rural watersheds.

• 한국경영과학회지
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• 제24권1호
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• pp.99-117
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• 1999

Since query language is used as a handy tool to obtain information from a database, a more intelligent query answering system is needed to provide user-friendly and fault-tolerant human-machine Interface. Frequently, database users prefer less rigid querying structure, one which allows for vagueness in composing queries, and want the system to understand the intent behind a query. When there is no matching data available, users would rather receive approximate answers than a null information response. This paper presents a knowledge abstraction database that facilitates the development of such a fault-tolerant and intelligent database system. The proposed knowledge abstraction database adepts a multilevel knowledge representation scheme called the knowledge abstraction hierarchy(KAH), extracts semantic data relationships from the underlying database, and provides query transformation mechanisms using query generalization and specialization steps. In cooperation with the underlying database, the knowledge abstraction database accepts vague queries and allows users to pose approximate queries as well as conceptually abstract queries. Specifically. four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual Join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• 한국수학교육학회지시리즈A:수학교육
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• 제49권3호
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• pp.299-311
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• 2010

The purpose of this study was to examine the effects of abstraction offer of basic concept principle and feedback of self-efficacy attributional and mathematical study ability of math underachievers in high school based on the attribution theory and self-efficacy theory. The hypothesis were posed as below : Hypothesis 1: The experimental group that takes the abstraction offer of concept principle and attributional feedback training would be better at most self-efficacy than the control group that doesn't. Hypothesis 2: The experimental group that takes the abstraction offer of concept principle and attributional feedback training would have better math achievement than the control group that doesn't. They were divided into an experimental group and a control group, and the attribution disposition, self-efficacy and academic achievement of the children were measured by pretest and posttest. For data analysis, SPSS/PC+ program was employed and t-test was conducted. The main findings of this study were as below : First, the abstraction offer of concept principle and attributional feedback training was effective for enhancing the math self-efficacy in high school underachievers. Second, the abstraction offer of concept principle and attributional feedback training was effective for increasing the math achievement in high school underachievers.

• 정보과학회 논문지
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• 제43권6호
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• pp.710-717
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• 2016

최근 여러 사물 인터넷 서비스가 사물 장치를 공유하는 다중 서비스 시스템을 구현하기 위해, 다양한 구조의 사물 추상화 프레임워크들이 제시되었다. 분산형 구조는 사물 인터넷 서비스 중복 문제가 있으며, 클라우드 서버 중심 구조는 실시간 인터랙션을 할 수 없다. 또한, 기존의 포그 서버 중심 구조에서는 불완전한 인터페이스가 사용되었다. 본 논문에서는 기존 구조의 문제를 해결한 사물 추상화 프레임워크인 Smart Fog를 제안하였다. Smart Fog는 스마트 게이트웨이와 3개의 IoT 인터페이스들로 구성된다. Smart Fog는 IoTivity와 OIC 표준을 기반으로 구현되었고, 이를 이용하여 실제 임베디드 장치인 Odroid-XU3에서 프로토타입을 구현하였다. 프로토타입 상에서 실험한 결과, Smart Fog가 실시간 인터랙션이 가능할 정도로 네트워크 지연 시간이 짧고, 분산형 구조에 비해 모바일 장치에서 발생하는 네트워크 트래픽이 74%, 전력 소모가 21% 감소함을 확인하였다.

• Spatial Information Research
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• 제10권3호
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• pp.421-438
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• 2002

GIS을 활용하는 다양한 응용분야에서 공간데이터베이스의 상세한 정도(추상화 수준)는 그 목적에 따라 달라진다. 추상화 수준이 달라지면 공간자료의 기하학적인 단순화뿐 아니라, 객체(인스턴스), 공간 및 속성 자료, 위상관계, 의미관계 등이 변화되거나 유지되어야 한다. 이와 관련하여 본 연구에서는 원시 공간데이터베이스를 추상화하여 목표데이터베이스를 생성하는 방법을 제시하였다. 공간데이터베이스를 추상화하는 연산자를 재정의하고, 어떤 객체에 어떤 연산자들을 어떤 순서로 적용하여야 하는지에 대한 기준을 제시하고, 이 기준에 따라 워크플로우를 제시하였으며, 프로토타입시스템을 개발하여 타당성을 검토했다.

• 정보처리학회논문지D
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• 제13D권1호
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• pp.111-116
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• 2006

주어진 상태가 도달 가능한지를 판정하는 작업은 모델 체킹과 같은 유한 상태 모델의 분석에서 필수적이다 만일 모델의 크기가 작다면 상태 공간을 전부 조사해서 판정할 수 있지만, 크기가 큰 경우에는 전체 상태 공간을 조사하는 것이 어렵거나 불가능할 수 있다. 이런 경우, 도달성 여부를 조사하기 전에 추상화를 통해서 모델을 축소해야 하며 이때 사용된 추상화는 false positive 오류를 허용하지 않는다. 본 논문에서는 이러한 추상화를 고안하여 네모라이즈 게임 풀이에 적용하였다. 그 결과, 상태 폭발 문제로 풀 수 없었던 큰 규모의 문제를 추상화를 통해서 해결할 수 있었다.

• 한국콘텐츠학회논문지
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• 제11권4호
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• pp.414-427
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• 2011

본 연구는 컷오프 수준에 따라 활성화 셀(cell) 수와 래더(ladder) 수 등의 통계량의 변화를 살펴보고, 컷오프 수준의 변화에 따른 가치 맵이 어떻게 변화하는지를 제시하며, 주어진 조건(100명의 응답자에게 최대 5개의 중요한 속성을 선택하도록 하여 가치사슬을 만든 후 이를 이용하여 가치 맵을 그렸을 경우)하에서 정보손실을 최소화하면서 설명력이 있는 최적의 컷오프 수준 결정과 이에 따른 가치 맵을 표현하고자 한다.

• 대한수학교육학회지:수학교육학연구
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• 제15권1호
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• pp.1-19
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• 2005

학생들이 수학을 추상적인 교과로 인식하여 학습에 흥미를 잃거나 실세계 문제를 해결하는 능력이 부족하다는 점이 문제시되어 왔다. 이에 본 연구에서는 사례연구 방법으로 학생들이 모델링 활동을 하는 과정에서 개발하는 모델이 구체와 추상을 연결하는 중재 기능을 할 수 있는지를 조사하였다. 연구결과, 학생들이 개발하는 모델은 탈맥락화 된 추상적 실체라기보다는 구체와 추상이 연결된 관계 망인 상황화된 추상의 영역에 위치하고 있었다. 그러므로 이 모델은 구체와 추상을 연결하는 중재기능을 할 수 있고, 학생들의 모델링 경험이 실세계 문제를 해결하는 능력을 향상시킬 수 있다고 볼 수 있다.

• Journal of Computing Science and Engineering
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• 제9권1호
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• pp.9-19
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• 2015

The most important challenge in the region-based abstraction method as an approach to compute the state space of time Petri Nets (TPNs) for model checking is that the method results in a huge number of regions, causing a state explosion problem. Thus, region-based abstraction methods are not appropriate for use in developing practical tools. To address this limitation, this paper applies a modification to the basic region abstraction method to be used specially for computing the state space of TPN models, so that the number of regions becomes smaller than that of the situations in which the current methods are applied. The proposed approach is based on the special features of TPN that helps us to construct suitable and small region graphs that preserve the time properties of TPN. To achieve this, we use TPN-TCTL as a timed extension of CTL for specifying a subset of properties in TPN models. Then, for model checking TPN-TCTL properties on TPN models, CTL model checking is used on TPN models by translating TPN-TCTL to the equivalent CTL. Finally, we compare our proposed method with the current region-based abstraction methods proposed for TPN models in terms of the size of the resulting region graph.

• 산업경영시스템학회지
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• 제21권46호
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• pp.181-196
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• 1998

The aim of this research is the development of a CAPP system which can use the old experience of process planning to generate a process plan for a new part and learn from its own experience using the concept of stratified case-based reasoning(CBR). A process plan is determined through the hierarchical process planning procedure that is based on the hierarchical feature structure of a part. Each part and case have their own multiple abstractions that are determined by the feature structure of the part. Retrieving the case in stratified case-based process planning is accomplished by retrieving the abstraction that is most similar to the input part abstraction in each abstraction level of the case-base. A new process plan is made by the adaptation that translates the old case's process plan into the process plan of a new part. Operations, machines and tools, setups and operation sequence in each setup are determined in the adaptation of abstraction using some algorithms and the reasoning based on knowledge-base. By saving a new part and its process plan as a case, the system can use this new case in the future to generate a process plan of a similar part. That is, the system can learn its own experience of process planning. A new case is stored by adding the new abstractions that are required to save as the new abstraction to the existing abstractions in the case-base.