• The Mathematical Education
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• v.36 no.1
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• pp.23-33
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• 1997

현대의 많은 교육학자나 심리학자들은 구성주의를 지지하고 있다. 구성주의는 학습이 행동주의에서 말하는 것과 같이 자극에 대해 수동적으로 일어나는 것이 아니라, 자기를 둘러싸고 있는 환경과 자기가 가지고 있는 인지상태의 평형을 이루기 위해 노력하는 능동적인 과정에 의하여 이루어진다는 가설을 이론으로 삼고 있다.(중략)

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.340-340
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• 2019

지구온난화로 유발되는 기후변동성이 증가함에 따라서 정확한 수문인자의 예측은 전 세계적으로 주요 관심사항이 되고 있다. 최근에는 고성능 컴퓨터 자원의 증가로 수문기상학 연구에서 동일한 학습량에 비하여 정확도의 향상이 뚜렷한 기계학습 구조를 활용하여 위성영상 기반의 대기예측, 태풍위치 추적 및 강수량 예측 등의 연구가 활발하게 진행되고 있다. 본 연구에는 기계학습 중 시계열 분석에 널리 활용되고 있는 순환신경망(Recurrent Neural Network, RNN) 기법의 대표적인 LSTM(Long Short-Term Memory) 네트워크를 이용하여 수문인자를 예측하였다. LSTM 네트워크는 가중치 및 메모리 요소에 대한 추가정보를 셀 상태에 저장하고 시계열의 길이 조정하여 모형의 탄력적 활용이 가능하다. LSTM 네트워크를 이용한 다양한 수문인자 예측결과 RMSE의 개선을 확인하였다. 따라서 본 연구를 통하여 개발된 기계학습을 통한 수문인자 예측기술은 권역별 수계별 홍수 및 가뭄대응 계획을 능동적으로 수립하는데 활용될 것으로 판단된다. 향후 연구에서는 LSTM의 입력영역을 Bayesian 추론기법을 활용하여 구성함으로 학습과정의 불확실성을 정량적으로 제어하고자 한다.

• Journal of The Korean Association of Information Education
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• v.4 no.2
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• pp.187-201
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• 2001

A project learning is the model to solve the problem in cooperation with the members of a group. The purpose of this study is to make a new learning model using a web on the traditional project learning model. A Web has the proper nature for students to make their learning environment, so that this study embodied Student Directed Web based project learning system to allow them to expand their abilities. All action of students, that is, suggesting main subject, making plans, activating and adjusting them, and evaluation can be happened in this system. According to the result of applying the system, participants in Students Directed Web based Project Learning intend to implement learning activities more positively, affirmatively and cooperatively than the existing ones.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.119-126
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• 2007

This paper presents a study investigating the effects of VR learning style on user attention and memory. The study involved users performed the guided or unguided style learning in the virtual environment while user attention was measured through physiological sensors (EEG, ECG, and GSR) and an eye tracking system. The users experienced the five specific events in a virtual environment associated with different stimuli, while they were given more specific goals during the guided task whereas they were given more goal asking them to actively search for the interesting items during the unguided task. The subject's attentions workload, feelings, memories about VR experience were measured by using a variety of physiological sensors during the task, video analysis, and post test survey. The results showed that the unguided task followed by the guided task made a considerable learning effect by giving a preview effect to the user. Moreover, the guided task drew more user attention and mental workload than the unguided task did.

• Journal of The Korean Association of Information Education
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• v.15 no.2
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• pp.179-188
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• 2011

The purpose of this thesis was to implement effective blended PBL(Problem-Based Learning) systems for information communication ethics education. The proposed systems, Online learning and face-to-face classes were systematically combined and Moodle is used for online learning platform. We proposed the use of wikis and blogs not just for creation of knowledge, but as active learning tool to support PBL. In the proposed system, learners used the web 2.0 as a open place to create new knowledge and experience various effects of PBL, such as (1) Improvement of problem solving ability, (2) Understanding of cooperative learning. The blended PBL systems with teaching and learning model were evaluated learners' level of satisfaction and educational achievement in the study of information communication ethics. The result shows that blended PBL learning method is more effective in cultivating consciousness of information communication ethics and showed more higher level of learners' satisfaction and educational achievement than the face-to-face PBL learning method.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.591-600
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• 2015

Recently high interest in health and fitness has led to vibrant researches for the active fitness system to learn and enjoy the exercise program for oneself. In this paper, we design and implement the active spinning training system which enables user to have self-learning and experience of customized spinning training program by the biometric and movement information acquired from user's physiological signals. The proposed system provides the appropriate difficulty of spinning program which reflects the concordance rate of spinning dance gestures and the amount of exercising by analyzing the physical status of participant from his brain and pulse waves and recognizing the skeletal movement in real time. For the higher exercise effect, the system offers a virtual personal trainer to show the correct poses and controls the level of difficulty depending on the concordance rate of participant's motions. The experiment with various participants through the proposed system shows that it is able to help users in getting the available exercise effect in comparatively short time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.23-34
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• 2004

In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

• Journal of KIISE
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• v.43 no.7
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• pp.795-800
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• 2016

In image classification, recent CNNs compete with human performance. However, there are limitations in more general recognition. Herein we deal with indoor images that contain too much information to be directly processed and require information reduction before recognition. To reduce the amount of data processing, typically variational inference or variational Bayesian methods are suggested for object detection. However, these methods suffer from the difficulty of marginalizing over the given space. In this study, we propose an image-text integrated recognition system using active vision based on Spatial Transformer Networks. The system attempts to efficiently sample a partial region of a given image for a given language information. Our experimental results demonstrate a significant improvement over traditional approaches. We also discuss the results of qualitative analysis of sampled images, model characteristics, and its limitations.

• Journal of the Korean School Mathematics Society
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• v.17 no.4
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• pp.565-587
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• 2014

Self-Regulated Learning Strategy is a kind of learning strategy that learners could choose and apply metacognitive, cognitive, motivational, and behavioral strategy autonomically and could take an active part in the classes. The purpose of the study was to identify aspects of self-regulated learning strategy with mathematical journal writing. Mathematical journal was composed of 13 questions and each of factor had 1~2 questions. The results of the study have revealed that metacognitive strategies were identified as setting up learning goals, seeking problem solving strategies, reflective thinking and providing examples. Cognitive strategy was identified as understanding the structure among ideas, sequential ranking and key ideas. Motivational strategy was identified as satisfaction and anxiety for studies, confidence and frustration for next studies. There are implications for mathematics education that self-regulated learning strategy can be improved with mathematical journal writing and help students to study mathematics efficiently and successfully.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.217-226
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• 2004

This paper describes an experiment of concrete and specific group work learning system based on the traditional Jigsaw group work learning model. Jigsaw model has two groups of students such as random group and expert group so that a course can make progress on explaining and lecturing all members of class after each student can be a member of expert group of course topic. We design and implement Web-based training system to support collaboration and Interaction among students of a course based on Jigsaw model The Web- based learning system makes each group going up to the expert level of a course subject by supporting various study menu and provides equal opportunity of improving social abilities such as leadership, communication skill, trust, and trouble-settling by taking part in collaboration activities.