• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.105-112
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• 2002

The purpose of this paper is to develop a courseware based on GIS (Geographic Information System) for improving visual and spatial learning efficiency of geography learning. The existing coursewares are not easy to encourage the learners in learning motivation, because these provide only the visual information using simple texts or imamges to the learners. To overcome these constraints, our courseware using GIS that can support spatial information can control the attribute information of map. In this paper, we define the courseware as the geography learning system. This courseware system enables the learners to take the perfect learning and the repetitive learning through the feedback after evaluating the learning degree. Also using geography learning application modules we implemented, the learners can participate directly in learning as well as search information in WWW.

• Korean Journal of Cognitive Science
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• v.7 no.3
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• pp.115-134
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• 1996

The study was designed to investigate implicit and explicit memory for words with processing theory.From experiment 1 to experiment 3,in a study phase,subjects first viewed stimulus words and were required to rate likeness of words of semantic processing task and to count lines of words of perceptual processing task.In a test phase,subjects were tested by implicit word completion task and explicit cued recall task.In experiment 1,levels of processing (LOP)effects were examined.Lop effects were obtained on the explicit memory tasks but not on the implicit memory tasks.In experiment 2,repertition of perceptual processing task influenced onlu implicit memory task.In experiment 3,bepertiotion of semantic processing task affected both implicit memory task and explicit memory task.These findings suggest that repetition effect of stimulus words are explanied better in dual process theory than transfer-appropriate processing theory.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.1-7
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• 2002

In this paper, an extended type of a direct learning control(DLC) method is proposed for the effective control of systems which perform a given task repetitively. DLC methods have been suggested to overcome the defects of iterative learning control, the learning process should be resumed from the beginning even if a slight change occurs in the desired output pattern. If a given desired output trajectory is "proportional" to the output trajectories which are learned previously, we can obtain the desired control input directly without the iterative learning process by using the DLC. First, most existing DLC methods are shown to be applicable only to single-input single-output systems with the relative degree one and then, an extended type of DLC is proposed for a class of nonlinear systems having the relative degree more than or equal to one by using the known relative degree of a nonlinear system. By the simulation results for the arbitrary nonlinear system with the relative degree more than one, the validity and the performance of the proposed DLC method are examined.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.603-625
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• 2010

Neural representation of a visual object is distributed across visual cortex and overlapped with those of many other objects. Thus repeating an object facilitates the recognition of the object while it impairs the recognition of other objects. These effects are called repetition priming and antipriming, respectively. Two experiments investigated a new phenomenon of repetition antipriming, in which a repeated object itself is antiprimed. The learning stage presented object pictures which were degraded at various levels. Participants determined how recognizable each object was. Then, the test stage presented the intact version of the object pictures and made participants to perform a categorization task. Both Experiment 1 and 2 found that the processing of the objects that had been recognized were facilitated (repetition priming) while the processing of the objects that had been perceptually ambiguous were impaired (repetition antipriming). These findings suggest that experiencing a perceptually ambiguous object might enhance the connection between feature-level representations and multiple object-level representations, which impairs the subsequent recognition of the repeated object.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.863-865
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• 2003

교육정보화의 실현이라는 과제가 현재의 학교현장에 필요한 만큼 제7차 교육과정의 시작과 더불어 학습자의 지식과 능력을 육성하기 위한 미리 계획된 WBI(Web based Instruction)를 기반으로 한 교수 모형의 필요성이 강조된다. 본 연구는 WBI의 교육적 기능을 충분히 반영하여 교실에서 교사가 사용하기 쉽고 효율적인 학습자료를 구현하여 웹 환경이 조성된 교실에서 활용할 수 있도록 하였다. 이러한 구현을 위한 프로그램으로는 웹 환경에서 실행하는데 무리가 없고 소용량으로 에니메이션 효과를 극대화 할 수 있는 Flash MX를 사용하였고, 고등학교 ‘수학10-나’의 내용 중 교과서와 칠판만을 사용하여 수업하는 데는 한계가 있는 과정인 ‘도형의 이동과 부등식의 영역’을 주로 개발하였다. 학습자들은 학교에서 수업한 내용을 웹 환경을 이용하여 개별학습 및 반복학습을 할 수 있고, 교사들은 교실이나 멀티미디어실에서 웹을 통하여 본 연구에서 구현한 프로그램을 사용함으로 학교 수업의 효율성을 높이고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.854-857
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• 2022

본 논문에서는 기존 이미지를 통해 위상 홀로그램을 생성하는 네트워크를 학습 및 최적화하여, 기존에 사용하는 알고리즘 방식인 GS 알고리즘(Gerchberg-Saxton algorithm)을 대체하는 것을 목표로 한다. GS는 반복 최적화 기법으로 한 장의 이미지에서 위상 홀로그램을 생성하는데 많은 시간이 걸리지만, 심층 학습 기반으로 학습된 모델을 통해 위상 홀로그램을 생성할 경우, 반복 최적화 과정 없이 짧은 시간 안에 위상 홀로그램을 생성할 수 있다. GS와 심층 학습 기반으로 각각 생성한 위상 홀로그램을 ASM(Angular Spectrum Method)을 통해 수치적으로 재복원하여 PSNR로 원본 이미지와 비교한 결과, 심층 학습 기반으로 생성한 위상 홀로그램에서 더 좋은 화질의 이미지를 짧은 시간 안에 얻을 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.211-218
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• 2011

Although the disaster management of Korea such as mitigation of disasters, preparedness for them and recovery from them. It should be considered based on the failures of the disaster management and the past experimental knowledge, it is believed that the repetitive occurrence of similar disasters is caused by absence of learning of disaster management organizational. That is, non-learning of the management organs due to experimental errors indicates that the organization themselves are not able to adjust to environment and the same kinds of disasters may happen in the future. Therefore, this study identifies repetitive failures by analysing reasons of the failures in terms of organizational learning in order to prevent from repetition of similar failures, and presents suggestions on the policy of disaster management. For the purposes, it carries both bibliographical analysis and case analysis. this study targets Daegu Subway Fire in 2003.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.133-140
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• 2016

This paper suggests designing how to acquire English vocabularies on the smart devices based on the research that a ground-breaking English Vocabulary Learning Contents needs developing. The method makes it possible to develop the contents which helps the learners to master English vocabularies effectively on the smart phone. The core idea of this paper is as in the following: 1) English learners learn 30 vocabularies for three minutes 10 times (one is for a new learning and the other nine ones are for reviews about the first learning) a day. 2) Considering Ebbinghaus Forgetting Curve, the reflection study proposes to provide the learners with three times' reviews: one day, 10days, and 30days later from which they learn the first 30 vocabularies. This contents is mainly made up of 5 developing sections (1)to generate App ID, (2)to access App, (3)to set up Alarm, (4)to process Word learning, and (5)to monitor the result of learning. This proposed idea is optimized to enhance the memory by Ebbinghaus Periodic Repetitive Method, which makes the learners satisfied with their English vocabulary learning.

• Journal of IKEEE
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• v.20 no.1
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• pp.94-102
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• 2016

This paper proposes a new prediction method to reduce times and labor of repetitive multi-physics simulation. To achieve exact results from the whole simulation processes, complex modeling and huge amounts of time are required. Current multi-physics analysis focuses on the simulation method itself and the simulation environment to reduce times and labor. However this paper proposes an alternative way to reduce simulation times and labor by exploiting machine learning algorithm trained with data set from simulation results. Through comparing each machine learning algorithm, Gaussian Process Regression showed the best performance with under 100 training data and how similar results can be achieved through machine-learning without a complex simulation process. Given trained machine learning algorithm, it's possible to predict the result after changing some features of the simulation model just in a few second. This new method will be helpful to effectively reduce simulation times and labor because it can predict the results before more simulation.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.725-728
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• 2002

현재, 웹기반 원격교육 시스템에서는 많은 학습자의 컨텐츠 및 서비스가 요구되고 있다. 기본 학습자료의 제공에 대한 많은 모형이 대두되고 있으나 기본 학습을 뒷받침해 줄 수 있는 보충학습 자료의 모형은 제시되지 않고 있다. 따라서, 본 논문에서는 학습자의 학습 휴리스틱에 의하여 기계학습된 보충학습 내용과 위치를 웹과 이메일로 자동 푸쉬해 줄 수 있는 시스템을 제안한다. 휴리스틱에 의하여 보충학습 데이터의 트리를 구성한 후 시멘틱 네트를 이용한 속성을 정의하고 기계학습된 학습자의 반복 학습 경로를 분석하여 보충학습을 원활히 진행할 수 있도록 시스템을 설계하는 것이 본 논문의 목적이다.