• Journal of Digital Convergence
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• v.13 no.1
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• pp.227-235
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• 2015

Big data analysis is a means of organizational problem solving. For an effective problem solving, approaches to problem solving should take into account the factors such as characteristics of problem, types and availability of data, data analytic capability, and technical capability. In this article we propose three approaches: logical top-down, data driven bottom-up, and prototyping for overcoming undefined problem circumstances. In particular we look into the relationship of creative problem solving with the bottom-up approach. Based on the organizational data governance and data analytic capability, we also derive strategic issues concerning the sourcing of big data analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.178-180
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• 2003

최소 걸침 나무는 널리 알려진 순회 판매원 문제와 같이 전통적인 최적화 문제 중에 하나이다. 특히나 최소 걸침 나무와는 달리 차수 제약 최소 걸침 나무의 경우는 일반적으로 NP-hard 문제로 알려져 있다. 이러한 NP-hard 문제를 해결하기 위한 다양한 접근법들이 소개되었는데 유전 알고리즘은 효율적인 방법 중에 하나로 알려져 있다. 유전 알고리즘과 같이 진화에 기반을 둔 알고리즘을 어떤 문제에 적응하기 위해서 가장 우선적으로 고려되어야 하는 것은 해를 어떻게 표현할 것인가 인데 본 논문에서는 차수 제약 최소 걸침 나무를 해결하기 위한 새로운 트리 표현법을 제안한다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.37-48
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• 2022

In this study, a hybrid meta-heuristic approach is proposed for solving engineering design optimization problems. Various approaches in many literatures have been proposed to solve engineering optimization problems with various types of decision variables and complex constraints. Unfortunately, however, their efficiencies for locating optimal solution do not be highly improved. Therefore, we propose a hybrid meta-heuristic approach for improving their weaknesses. the proposed GA-VNS-HC approach is combining genetic algorithm (GA) for global search with variable neighborhood search (VNS) and hill climbing (HC) for local search. In case study, various types of engineering design optimization problems are used for proving the efficiency of the proposed GA-VNS-HC approach

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

• School Mathematics
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• v.5 no.3
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• pp.343-360
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• 2003

In this paper, we deal with the teaching of algebra based on patterns and generalization. The past algebra curriculum starts with letters(variables), algebraic expressions, and equations, but these formal approaching method has many difficulties in the school algebra. Therefore we insist the new algebraic approaches should be needed. In order to develop these instructions, we firstly investigate the relationship of patterns and algebra, the relationship of generalization and algebra, the steps of generalization from patterns and levels of difficulties. Next we look into the algebra instructions based arithmetic patterns, visual patterns and functional situations. We expect that these approaches help students learn algebra when they begin school algebra.

• Journal for History of Mathematics
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• v.32 no.6
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• pp.281-299
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• 2019

Mathematical problem solving has become a major concern in school mathematics, and methods to enhance children's mathematical problem solving abilities have been the main topics in many mathematics education researches. In addition to previous researches about problem solving, the development of a mathematical problem solving method that enables children to establish mathematical concepts through problem solving, to discover formalized principles associated with concepts, and to apply them to real world situations needs. For this purpose, I examined the necessity of problem solving education and reviewed mathematical problem solving researches and problem solving models for giving the theoretical backgrounds. This study suggested the problem solving approach based on the intuitive and the formal inquiry which are the basis of mathematical discovery and inquiry process. And it is developed to keep the balance and complement of the conceptual understanding and the procedural understanding respectively. In addition, it consisted of problem posing to apply the mathematical principles in the application stage.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.916-919
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• 2018

심층신경망 모델은 우수한 성능을 갖고 있음에도 불구하고 모델이 어떤 판단 과정을 통해 결론을 내렸는지 파악하기 어렵다. 그에 따라 판단에 대한 근거가 중요한 분야에서는 심층신경망 모델을 적용한 실제 사례를 찾기 어렵다. 인공신경망 모델을 해석하기 어렵다는 문제를 해결하기 위해 내부 구조를 이용하여 규칙을 추출하는 decompositional 접근법이 제안되었으나 기존의 연구는 대부분 은닉층이 1개인 다층 퍼셉트론 모델에서 규칙을 생성하는 것을 가정하고 있다. 오늘날 사용하는 심층신경망 모델은 일반적으로 여러 은닉층을 가지고 있기 때문에 기존의 접근법을 그대로 적용할 경우 규칙 불확실성에 따라 잘못된 규칙을 추출하는 문제가 발생한다. 본 논문은 decompositional 접근법에 존재하는 규칙 불확실성 문제를 완화하고 깊이가 깊은 심층신경망 모델에 규칙을 추출하는 방법을 제안한다. 제안한 접근법은 실제 활성화 값을 통해 지식을 추출하며, 이를 통해 규칙 불확실성 문제를 완화할 수 있었다.

• ICROS
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• v.19 no.2
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• pp.34-38
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• 2013

자연계에서 빈번히 목격되는 군집 현상과 그 효용성의 고찰에 기인하여, 최근 다중 이동 로봇의 협업에 대한 연구가 활발히 수행되고 있다. 그 중, 본 논문에서는 다중 이동 로봇의 군집 제어 방법론들을 설명하고, 그와 관련된 최신 결과들도 소개한다. 특히 군집 제어 문제를 해결하기 위한 대표적인 방식인 행동 기반 접근법, 가상 구조 접근법, 선도-추종 접근법, 그래프 이론 기반 접근법 위주로 소개한다.

• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.107-111
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• 2014

URI 중의성 해소 문제는 주어진 문서 내의 특정 단어에 연결 가능한 여러 URI가 주어졌을 때 진짜 URI 하나를 선택해내는 문제라고 할 수 있다. 이 문제는 다양한 해결법들이 존재할 수 있지만 기존에 연구된 문서의 문맥 간 유사도를 이용하여 해결하는 방법을 본 논문에서는 사용한다. 문맥 간 유사도를 이용하는 방법은 영어 디비피디아 URI spotting에서 TF*ICF방법으로 이미 연구가 되어있다. 본 논문에서는 Latent Dirichlet Allocation을 이용하여 URI 중의성 해소 문제를 다룰 것이며 그 범위를 한국어 디비피디아로 한정한다. 새로 제안하는 방법이 URI 중의성 해소 문제를 얼마나 잘 해결하며, 기존의 연구와 비교하여 얼마나 향상될 수 있는지를 분석한다. 또한 기존의 방법과 새로 제안한 방법 각자가 고유하게 풀 수 있는 문제가 존재함을 보이고, 두 방법을 병합하였을 때 보다 높은 성능에 도달할 수 있음을 전망한다.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.268-276
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• 2005

This paper deals with optimum communication spanning tree(OCST) problem. Generally, OCST problem is known as NP-hard problem and recently, it is reveled as MAX SNP hard by Papadimitriou and Yannakakis. Nevertheless, many researchers have used polynomial approximation algorithm for solving this problem. This paper uses evolutionary algorithm. Especially, when an evolutionary algorithm is applied to tree network problem such as the OCST problem, representation and genetic operator should be considered simultaneously because they affect greatly the performance of algorithm. So, we introduce a new representation method to improve the weakness of previous representation which is proposed for solving the degree constrained minimum spanning tree problem. And we also propose a new decoding method to generate a reliable tree using the proposed representation. And then, for finding a suitable genetic operator which works well on the proposed representation, we tested three kinds of genetic operators using the information of network or the genetic information of parents. Consequently, we could confirm that the proposed method gives better results than the previous methods.