• Wind and Structures
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• v.6 no.6
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• pp.437-450
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• 2003

In this paper, the structural random response due to the turbulent boundary layer excitation is investigated. Using the mode shapes and natural frequencies of an undamped structural operator, a fully analytical model has been assembled. The auto and cross-spectral densities of kinematic quantities are so determined through exact analytical expansions. In order to reduce the computational costs associated with the needed number of modes, it has been tested an innovative methodology based on a scaling procedure. In fact, by using a reduced spatial domain and defining accordingly an augmented artificial damping, it is possible to get the same energy response with reduced computational costs. The item to be checked was the power spectral density of the displacement response for a flexural simply supported beam; the very simple structure was selected just to highlight the main characteristics of the technique. In principle, it can be applied successfully to any quantity derived from the modal operators. The criterion and the rule of scaling the domain are also presented, investigated and discussed. The obtained results are encouraging and they allow thinking successfully to the definition of procedure that could represent a bridge between modal and energy methods.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.335-340
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• 2021

This study conducted research on creating an environment for maker education programs for robot and SW education, development and application of maker education programs for low-grade elementary school students in farming and fishing villages. Based on the preceding maker education model, the OMCSI model was developed for the lower grade level of elementary school, and based on this, five WeDo-utilized elementary maker education programs were developed. From April 1, 2020 to October 30, 2020, the results of applying the elementary school maker education program using WeDo Robot 2.0 to 10 second graders of 10 Elementary School in Gyeongsangnam-do are as follows. The average increased by 3.40 points (t=-2.378, p=0.034) and the average increased by 3.30 points (t=-2.329, p=0.040). The average was also increased by 3.40 points (t=-2.458, p=0.038). Finally, it rose to 3.70 points (t=-2.449, p=0.037) for its reasoning ability. That is, all four sub-elements of computing thinking had a significant probability of 0.04, indicating statistical significant differences between scores of pre-post computing thinking. Therefore, the Elementary Maker Education Program using WeDo robots has worked very effectively to improve students' computing thinking skills.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.708-711
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• 1997

This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

• Proceedings of The KACE
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• 2017.08a
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• pp.107-109
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• 2017

다가올 미래 사회와 4차 산업혁명 시대에는 창의성(Creation)과 융합(Convergence)을 기반으로 다양한 분야에서의 문제해결력이 요구되며, 컴퓨팅 사고력(CT, Computational Thinking)은 문제 해결을 위한 필수 사고로 인식되고 있다. 이러한 시대적 흐름에 발맞춰, 성균SW교육원(SSEN)에서는 다른 전공을 가진 학생에게도 컴퓨팅 사고력 중심의 SW기초교육을 실시하고 있다. 본 논문에서는 성균SW교육원에서 시행하는 비전공자를 위한 컴퓨팅사고력 중심의 SW기초교육 체계에 대해 소개하고, 비전공자 SW교육에 대해 앞으로 나아갈 방향을 제시한다.

• Proceedings of The KACE
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• 2017.08a
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• pp.251-252
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• 2017

본 논문에서는 컴퓨팅 사고력을 향상시키는 방안에 대한 교사들의 강의안에 대한 여러 가지 사례를 분석하였다. 연수에 참여한 정보 컴퓨터(특수 정보 컴퓨터 7명 포함) 교사 37명을 대상으로 실제 학교 현장에서 학생들을 대상으로 컴퓨팅 사고력을 향상시키는 여러 가지 방안을 제시한 후, 산출물을 분석하였다. 산출물 분석 결과 댄스 활동과 같은 학생들이 재미있어 하는 분야를 발굴하는 방법, 글쓰기와 같은 컴퓨터와 상관없는 일상생활의 사례를 활용하여 글쓰기 대회에 입상하는 사례, 수학여행 계획을 여러 학생이 함께 참여하여 완성하는 방법 등을 제시하였다. 본 논문에서는 여러 가지 사례들을 소개하고 사례들에서 컴퓨팅 사고력을 향상시키는 방안의 공통적인 요인을 도출하여 보고자 한다.

• Proceedings of The KACE
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• 2017.08a
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• pp.11-13
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• 2017

컴퓨팅 사고력은 제 4차 산업혁명 시대에 접어든 우리 사회에서 필요로 하는 미래 역량으로 꼽히고 있으며, 우리나라에서도 2015 개정 문이과 통합형 교육과정을 통해 컴퓨팅 사고력 신장을 위한 SW교육을 강조하고 있다. 3D 모델링 교육은 컴퓨팅 사고력과 직접적인 관련이 있다. 3D 모델링을 위하여 실제의 구체물을 단순화 하거나, 모델링을 위하여 필요 없는 부분을 삭제하거나 추가하는 것이 컴퓨팅 사고력의 추상화에 해당된다. 그리고 모델링 프로그램을 사용하는 것은 일종의 자동화에 해당된다. 본 연구에서는 컴퓨팅 사고력 신장을 위한 3D 모델링 교육에서 권장할만한 3D 모델링 프로그램을 틴커캐드(TinkerCad)로 제시하였으며, 컴퓨팅 사고력 신장을 위한 틴커캐드 활용 초등 3D 모델링 교육 방법을 제시하였다.

• Journal of The Korean Association of Information Education
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• v.17 no.2
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• pp.125-134
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• 2013

In this paper, we want to know the effect of elementary students' creativity thru the play-centered computer science educational program. We extracted educational content from computer science. The students addressed to the problems thru the play and found their own solution. Research result show significant difference in creative attitude of sub-area of creativity. We found that students were actively involved with pleasure in play, the rules of play was actively keep.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.633-640
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• 2001

In this paper we examine the machine learning issues raised by the domain of the Intrusion Detection Systems(IDS), which have difficulty successfully classifying intruders. There systems also require a significant amount of computational overhead making it difficult to create robust real-time IDS. Machine learning techniques can reduce the human effort required to build these systems and can improve their performance. Genetic algorithms are used to improve the performance of search problems, while data mining has been used for data analysis. Data Mining is the exploration and analysis of large quantities of data to discover meaningful patterns and rules. Among the tasks for data mining, we concentrate the classification task. Since classification is the basic element of human way of thinking, it is a well-studied problem in a wide variety of application. In this paper, we propose a classifier system based on genetic algorithm, and the proposed system is evaluated by applying it to IDS problem related to classification task in data mining. We report our experiments in using these method on KDD audit data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.417-418
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• 2018

오늘날 SW 중심사회에서 컴퓨팅 사고력은 꼭 필요한 핵심역량으로 중요성이 강조되고 있으며, 이에 따라 2015 개정 교육과정에서는 소프트웨어(SW) 교육, 정보 교육을 강화하였다. 온라인 채점 시스템은 학생들이 문제해결 소스코드를 제출하면 이를 평가하고, 적절한 피드백을 제공하므로 자기주도적인 문제해결학습 경험과 프로그래밍 스킬을 향상시키는데 도움을 줄 수 있어 사용이 확대되고 있다. 그러나 채점시스템에 탑재된 문제들은 반구조화된 형태로 되어 있어 학생들이 컴퓨팅 사고단계 중 1단계인 문제공식화(추상화) 단계를 충분히 연습하지 못할 가능성이 있다. 본 논문에서는 이를 보완한 문제해결학습 학습모형을 제안하고, 논의한다.

• Research in Mathematical Education
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• v.1 no.1
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• pp.13-22
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• 1997

Cognitive psychology has provided valuable theoretical perspectives on learning mathematics. Based on the metaphor of the mind as an information processing device, educators and psychologists have developed detailed models of competence in a variety of areas of mathematical skill and understanding. Unquestionably, these models are an asset in thinking about the curriculum we want our students to follow. But any psychological paradigm has aspects of learning and knowledge that it accounts for well, and others that it accounts for less well. For instance, the paradigm of cognitive science gives us valuable models of the knowledge we want our students to acquire; but in picturing the mind as a computational device it reduces us to conceiving of learning in individualist terms. It is less useful in helping us develop effective learning communities in our classrooms. In this paper I review some of the significant accomplishments of cognitive psychology for mathematics education, and some of the directions that situated cognition theorists are taking in trying to understand knowing and learning in terms that blend individual and social perspectives.