• 한국초등수학교육학회지
• /
• 제17권1호
• /
• pp.105-128
• /
• 2013

우리나라 교육과정은 7차 이후 2007, 2009 개정 교육과정을 거치면서 다양한 변화를 모색하고 있다. 본 연구는 그 가운데 초등수학 교과서의 내용 변화에 주목하고 있으며, 특히 초등수학에서 다루어지고 있는 문자와 식에 초점을 맞추고 있다. 문자와 식은 6차 교육과정에서는 '관계' 영역에서, 7차 교육과정에서는 '문자와 식' 영역에서, 그리고 2007 교육과정에서는 '규칙성과 문제해결' 영역에서 다루어져왔다. 특히 7차 교육과정에서는 초등수학에서 문자가 도입되지 않았으나, 6차와 2007년 교육과정에서는 초등수학에서 문자 x의 도입, 등식의 성질, 방정식 등이 다루어지고 있다. 본 연구는 초등수학에서 이러한 변화를 겪고 있는 문자와 식에 대하여 교육과정별 교과서에 제시된 문자와 식의 내용 및 지도 시기, 지도 방법에 대한 분석을 목적으로 한다. 이를 위해 문자 x의 도입, 등식의 지도, 방정식의 지도와 같이 3가지 주제를 구분하고, 이들 각각에서 초등수학을 중심으로 6차 교육과정과 2007년 교육과정을 비교하고, 동시에 그 사이에 놓여 있는 7차 교육과정에서는 중학교 7-가 단계를 살펴보았다. 본 연구는 이를 통해 초등수학에서 문자와 식을 이해하고 지도하는데 기초자료가 될 수 있기를 기대한다.

• 한국초등수학교육학회지
• /
• 제18권3호
• /
• pp.459-474
• /
• 2014

본 연구는 초등학교 5학년 도형의 대칭 단원을 GSP 프로그램을 활용하여 지도했을 때, 도형의 대칭이동 학습과 자기 주도적 학습태도에 효과가 있는지를 알아보는데 그 목적이 있다. 이 연구를 위하여 실험집단은 GSP 프로그램을 활용하여 도형의 대칭을 학습하였고, 비교집단은 전통적인 방법으로 학습하였다. 그 결과 실험집단과 비교집단 간 수학 성취도와 자기 주도적 학습태도에서 매우 유의미한 차이가 있는 것으로 나타났다. 이는 GSP 프로그램을 활용하는 것이 도형의 대칭을 이해하는 데 많은 도움을 준다는 것을 의미한다. 또한 GSP 프로그램을 활용한 수업이 학생들에게 흥미를 불러 일으켰으며, 학생 스스로 문제를 탐구할 수 있는 기회를 제공하였음을 의미한다.

• 시스템엔지니어링학술지
• /
• 제15권2호
• /
• pp.31-38
• /
• 2019

The systems engineering standard process is intended to be customized for a given project environment and system characteristics. This study describes the experience gained by applying systems engineering to government-funded projects. The characteristics of government funded project are lack of common development process among the participating organizations and mechanism to determine system requirements. This study describes the contents of the systems engineering activities, including development of operational concept, system requirements, verification requirements (test cases), test verification plan, and implementation of system test and lessons learned from these activities.

• 한국게임학회 논문지
• /
• 제15권1호
• /
• pp.125-134
• /
• 2015

본 논문은 학습자가 효과적인 게임프로그래밍을 학습하도록 피어튜터모형(TGF: Tutoring Game program in Flipped learning)을 설계하고, 수업에 적용한 학습경험을 교수와 피어튜터 및 학습자의 관점에서 제시하고, 학습 성과를 설문조사를 통해 분석하여 플립드 러닝 환경에서의 TGF가 전통적인 수업방식에 비해 게임프로그래밍 수업에서 학습목표를 달성하는데 더욱 효과적임을 보였다.

• 한국윤활학회:학술대회논문집
• /
• 한국윤활학회 1998년도 제27회 춘계학술대회
• /
• pp.83-90
• /
• 1998

The morphologies of the wear debris are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify friction condition from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction coefficient. It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We dicuss between the characteristic of wear debris and the friction coefficient and how the network determines difference in wear debris feature.

• 한국윤활학회:학술대회논문집
• /
• 한국윤활학회 1997년도 제25회 춘계학술대회
• /
• pp.25-32
• /
• 1997

The neural network was applied to identify wear debris generated from the lubricated machine moving surface. The wear test was carried out under different experimental conditions. In order to describe characteristics of debris of various shapes and sizes. The four parameter(50% volumetric diameter, aspect, roundness and reflec- tivity) of wear debris are used as inputs to the network and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network.

• 천문학회보
• /
• 제42권2호
• /
• pp.45.1-45.1
• /
• 2017

A Korean VLBI Network Key Science Program, the Interferometric Monitoring of Gamma-ray Bright AGNs (iMOGABA) program continues to aim at revealing the origins of the gamma-ray flares that are often detected in active galactic nuclei (AGNs). Here in this presentation, we would like to present what we have learned about the Gamma-ray bright AGNs based on the recent results of the Korean VLBI Network Key Science Program: the iMGOABA. The results will include a) the source properties of the whole samples obtained from a single-epoch observation, and b) some of scientific highlights for the iMOGAGBA on specific sources. From those highlighted works, we find that the Gamma-ray bright AGNs become fainter at higher frequencies, yielding optically thin spectra at mm wavelengths. Based on the studies on specific sources, taking into account the synchrotron self-absorption model of the relativistic jet, we estimated the magnetic field strength in the mas emission region during the observing period.

• 한국생산제조학회지
• /
• 제7권4호
• /
• pp.42-49
• /
• 1998

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surface from which the particles originated. The morphological identification of wear debris can therefore provide very early detection of a fault and can also often facilitate a diagnosis. The purpose of this study is to attempt the developement of intelligent system for moving condition diagnosis of the machine driving system. The four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of war debris are used as inputs to the neural network and learned the moving condition of five values(material3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the moving condition and materials very well by neural network.

• 한국윤활학회:학술대회논문집
• /
• 한국윤활학회 1997년도 제26회 추계학술대회
• /
• pp.135-144
• /
• 1997

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surfaces from which the particles originated. The morphologies of the wear particles are therefore directly indica- rive of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We dicuss how the network determines difference in wear debris feature, and this approach can be applied to condition diagnosis of the lubricated moving system.

• 한국멀티미디어학회논문지
• /
• 제18권3호
• /
• pp.359-367
• /
• 2015

In this paper, we propose intelligent fire learning and detection system using hybrid visual attention mechanism of human. Proposed fire learning system generates leaned data by learning process of fire and smoke images. The features used as learning feature are selected among many features which are extracted based on bottom-up visual attention mechanism of human, and these features are modified as learned data by calculating average and standard variation of them. Proposed fire detection system uses learned data which is generated in fire learning system and features of input image to detect fire.