• 대한수학회지
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• 제38권6호
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• pp.1157-1166
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• 2001

This paper answers some old questions about approximate similarity and raises new ones. We provide positive evidence and a technique for finding negative evidence on the question of whether approximate similarity is the equivalence relation generated by approximate equivalence and similarity.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1999년도 춘계학술대회논문집
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• pp.71-75
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• 1999

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity geometrical size and die velocity of model materials are different from those of real materials. Actually the forming load of yoke which is an automobile part made of aluminum alloys(Al-6061) is predicted by using this approximate similarity theory. Firstly upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061) and a suitable model material is selected for model material test of Al-6061 And then and forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material which has been selected from above upset forging tests, The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• 한국정밀공학회지
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• 제17권1호
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• pp.204-208
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• 2000

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity, geometrical size, and die velocity of model materials are different from those of real materials. Actually, the forming load of yoke, which is an automobile part made of aluminum alloys(Al-6061), is predicted by using this approximate similarity theory. Firstly, upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061), and a suitable model material is selected for model material test of Al-6061. And then hot forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material, which has been selected from above upset forging tests. The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• Journal of Mechanical Science and Technology
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• 제15권9호
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• pp.1339-1345
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• 2001

Laminar film condensation of a saturated pure vapor in forced flow over a flat plate is analyzed as boundary layer solutions. Similarity solutions for some real fluids are presented as a function of modified Jakob number (C$\_$pι/ ΔΤ/Prh$\_$fg/) with property ratio (No Abstract.see full/text) and Pγ as parameters and compared with approximate solutions which were obtained from energy and momentum equations without convection and inertia terms in liquid flow. Approximate solutions agree well with the similarity solutions when the values of modified Jakob number are less then 0.1 near 1 atmospheric pressure.

• 정보보호학회논문지
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• 제25권3호
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• pp.595-602
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• 2015

디지털 포렌식 분야가 직면한 과제 중 하나는 대량의 데이터를 어떻게 효율적으로 처리할 것인가이다. 디지털 객체 간의 유사성을 빠르게 식별하기 위해 신뢰성 있는 다양한 근사 매칭 알고리즘이 계속하여 제시되어왔다. 하지만 알고리즘만으로 문자열의 의미적 유사성을 식별하면 많은 오탐을 보여 오히려 그 실효성을 끌어내리고 있다. 이와 같은 문제점을 해결하고자 근사 매칭 대상의 전처리 과정을 추가하여, 알고리즘 자체의 신뢰성은 유지하면서 유사도 탐지 정확성을 더 높일 수 있는 방법을 제시한다. 본 논문에서는 의미적 유사성을 식별하고자 eml과 hwp 세트를 가지고 sdhash로 실험하였으며, 실험 결과를 이용하여 그 효과성을 검증한다.

• 한국콘텐츠학회논문지
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• 제22권8호
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• pp.33-43
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• 2022

지식 그래프 및 단백질 상호 작용과 같은 실제 데이터에서 개체들과 개체들의 관계 및 구조를 나타내기 위해 레이블 그래프를 사용한다. IT의 급속한 발전과 데이터의 폭발적인 증가로 사용자에게 관심 있는 정보를 제공하기 위한 서브 그래프 매칭 기술이 필요하다. 본 논문은 레이블의 의미적 유사성과 그래프 구조 차이를 고려한 근사 Top-k 서브 그래프 매칭 기법을 제안한다. 제안하는 기법은 레이블 의미적 유사도를 고려하기 위하여 FastText을 활용한 학습 모델을 이용한다. 레이블 간 의미적 유사도를 미리 계산한 LSG(Label Similarity Graph)를 통해 처리 속도의 효율을 높인다. LSG를 통해 레이블이 정확하게 일치해야 확장이 가능한 기존 연구의 한계를 해결한다. 2-hop까지 탐색을 수행함으로써 질의 그래프에 대한 구조적 유사성을 지원한다. 매칭된 서브 그래프는 유사도 값 기반으로 Top-k 결과를 제공한다. 제안하는 기법의 우수성을 보이기 위하여 다양한 성능평가를 수행한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.719-724
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• 1998

This paper presents a systematic developement of a formal approach to inference in approximate reasoning. We introduce some measures of similarity and discuss their properties. Using the concept of similarity index we formulate two methods for inferring from vague knowledge. In order to illustrate the effectiveness of the proposed technique we use it to develop a vowel recognition system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1274-1276
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• 1993

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

• 전자공학회논문지C
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• 제34C권10호
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• pp.98-105
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• 1997

In this work, we proesent a bidirectional approximate reasoning method and fuzzy inference network for interval valued decision making systems. For this, we propose a new type of similarity measure between two fuzzy vectors based on the Ordered Weighted Averaging (OWA) operator. Since the proposed similarity measure has a structure to give the extreme values by choosing a suitable weighting vector of the OWA operator, it can render an interval valued similarity value. From this property, we derive a bidirectional approximate reasoning method based on the similarity measure and show its fuzzy inference network implementation for the decision making systems requiring the interval valued decisions.

• Journal of applied mathematics & informatics
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• 제26권3_4호
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• pp.493-500
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• 2008

In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.