• 산업공학
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• 제25권2호
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• pp.178-186
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• 2012

The DRAM module is an important part of servers, workstations and personal computer. Its malfunction causes a lot of damage on customer system. Therefore, customers demand the highest quality products. The company applies DRAM module Outgoing Quality Assurance Inspection(OQA) to secures the highest quality. It is the key process to decides shipment of products through sample inspection method with customer oriented tests. High fraction of defectives entering to OQA causes inevitable high quality cost. This article proposes the application of ensemble learning to classify the lot status to minimize the ratio of wrong decision in OQA, observing a potential in reducing the wrong decision.

• 상하수도학회지
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• 제35권1호
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• pp.93-100
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• 2021

Forward osmosis (FO) process is a chemical potential driven process, where highly concentrated draw solution (DS) is used to take water through semi-permeable membrane from feed solution (FS) with lower concentration. Recently, commercial FO membrane modules have been developed so that full-scale FO process can be applied to seawater desalination or water reuse. In order to design a real-scale FO plant, the performance prediction of FO membrane modules installed in the plant is essential. Especially, the flux prediction is the most important task because the amount of diluted draw solution and concentrate solution flowing out of FO modules can be expected from the flux. Through a previous study, a theoretical based FO module model to predict flux was developed. However it needs an intensive numerical calculation work and a fitting process to reflect a complex module geometry. The idea of this work is to introduce deep learning to predict flux of FO membrane modules using 116 experimental data set, which include six input variables (flow rate, pressure, and ion concentration of DS and FS) and one output variable (flux). The procedure of optimizing a deep learning model to minimize prediction error and overfitting problem was developed and tested. The optimized deep learning model (error of 3.87%) was found to predict flux better than the theoretical based FO module model (error of 10.13%) in the data set which were not used in machine learning.

• 한국지구과학회지
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• 제25권3호
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• pp.176-184
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• 2004

The concept of 'the lunar and planetary phases' is very difficult to understand and students may have various misconceptions on this concept. A module drawing the lunar and planetary phases was developed with the application of the simplifying conditions method. The effects of instruction using the module drawing the lunar and planetary phases on the conceptual change and the achievement was investigated in the consideration of learners' characteristics (spatial perception ability, science inquiry ability, required pre-requested learning ability). Findings were as follows: 1) This module was effective for learners' conceptual change and achievement, 2) This module had a positive influence for development the learners' characteristics and conceptual change with the middle level of science inquiry ability, the middle and low level of required pre-requisite learning ability, and middle level of the spatial perception ability.

• 컴퓨터교육학회논문지
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• 제8권2호
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• pp.33-40
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• 2005

기존 CAI(Computer Assisted Instruction) 학습방법에서의 문제점은 학습자의 개인적 특성을 충분히 고려하지 못한 채 교수설계자가 정한 학습 경로에 따라 학습하도록 구현되었다는 점이다. 이런 점을 해결하기 위해서는 시스템 설계 시 누적된 개인자료를 통하여 개인차를 지능적으로 판단하고, 결손 된 부분을 처방할 수 있는 인공지능을 갖춘 ITS(Intelligent Tutoring System)가 필요하다. 본 연구에서는 향후 시스템 설계자가 전자계산기구조 학습을 위한 시스템 설계 시 학습자가 학습과정에서 범할 수 있는 오류와 성취능력수준을 파악하여 수준별 학습이 가능토록 할 수 있는 학습자 모델링을 설계하는데 있어 고려하여야 할 요소들을 제시하였다.

• 한국전자통신학회논문지
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• 제9권9호
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• pp.999-1004
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• 2014

본 논문에서는 초보자들도 건반악기의 연주 방법을 쉽고, 효과적으로 학습할 수 있도록 건반악기 자율 학습 시스템을 개발하였다. 본 연구에서 개발한 지능형 건반악기 자율 학습시스템은 스마트폰 기반의 학습 어플리케이션과 건반악기 보조 모듈로 구성된다. 건반악기 보조 모듈은 스마트폰 어플리케이션과 블루투스 통신을 통하여 악기 연주 정보를 수신한 후, LED에 표시해 줌으로써 초보자도 쉽게 건반과 음계의 상관관계를 숙지할 수 있도록 하였다. 또한 사용자의 연주정보를 저장하고, 분석 정보를 제공하여 효과적인 학습이 가능하도록 구현하였다.

• 한국CDE학회논문집
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• 제2권2호
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• pp.111-121
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• 1997

This study intends to develop a fixture planning module as a part of the planning system for cutting. The fixture module uses machine learning method to reuse previous failure results so that the system can reduce the repeated failures. Machine learning is one of efforts to incorporate human reasoning ability into a computerized system. A human expert designs better than a novice does because he has a wide experience in a specific area. This study implements the machine learning algorithm to have a wide experience in the fixture planning area as a human expert does. When the fixture planner finds a setup failure for the suggested operations by a process planner, it makes the process planner store its attributes and other information for the failed setup. Then the process planner applies the learned knowledge when it meets a similar case so that the planner can reduce possibility of setup failure. Also the system can teach a novice user by showing a failed setup with a modified setup.

• 음성과학
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• 제14권3호
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• pp.31-46
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• 2007

This study attempts to investigate that the training of pitch manipulation would help Korean speakers reduce the intonation errors based on the review of many previous studies on Korean speakers' phonetic realization of intonation. The previous studies have indicated that Korean speakers have problems with pitch manipulation in their production of English word stress, sentence stress, and eventually intonation. To train Korean speakers phonetically realize English pitch patterns, a blended learning module was operated for two weeks: face-to-face instruction for six hours and e-learning instruction for three hours in total. This module was designed to help Korean speakers realize pitch as a distinctive phoneme. An acoustic assessment on five Korean female English speakers shows that the training of pitch manipulation helps Korean English speakers reduce the intonation errors indicated in the previous studies reviewed.

• 산업경영시스템학회지
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• 제30권4호
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• pp.133-140
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• 2007

This study aims to design and implement a learning evaluation system using .NET which is developed by Microsoft. .NET technology supports higher processing speed than ASP technology. The learning evaluation system is based on the web, consists of administrator module, questioner module and student module. The functions of the system, i.e., providing test questions, performing test, and evaluating result of test are achieving on the web in real time. Even when many users use this system, the system is stable and has a speed response time.

• 자연과학논문집
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• 제19권1호
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• pp.11-25
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• 2008

An Adobe Connect Meeting Moodle activity module was developed for the Pai-Chai Moodle virtual learning environment. Professors can create online meeting room directly from their courses by using the Adobe Connect Meeting module. The web services from the server was utilized for the application integration.

• 대한지구과학교육학회지
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• 제10권1호
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• pp.26-37
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• 2017

이 연구의 목적은 중등과학 예비교사들의 조석 개념에 대한 오개념을 조사하고, 오개념을 과학개념으로 변화시킬 수 있는 학습모듈을 개발하여 개념변화에 미치는 학습모듈의 효과를 검사하는 것이다. 이에 연구자는 연구의 목적을 달성하기 위해 조석 개념 검사지와 인지갈등 전략을 적용한 조석 개념 학습모듈을 개발하여 적용하였다. 연구대상은 G 광역시에 소재한 사범대학 과학교육 전공 1학년 학생 40명을 대상으로 하였다. 연구 결과는 다음과 같다. 첫째, 중등과학 예비교사들은 조석 현상에 대하여 다양한 오개념을 갖고 있었다. 둘째, 개발한 학습모듈은 중등과학 예비교사들의 조석에 대한 오개념을 과학개념으로 변화시키는데 효과적이었다. 그러나 일부 학생들은 모듈의 학습 후에도 조석에 대한 오개념을 갖고 있었다. 그중 대표적인 오개념은 지구와 달이 공통질량 중심을 회전 중심으로 공전할 때 발생하는 원심력을 지구 자전에 의한 원심력과 구별하지 못하는 것과 지구가 공통질량 중심을 회전 중심으로 공전하는 동안 지구의 자전을 고려하지 않아야 한다는 사실을 알지 못하는 것이었다.