• Journal of Computing Science and Engineering
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• 제3권4호
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• pp.218-237
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• 2009

Interactions are intrinsic part of what we do. We interact when we work, when we learn, when we visit a doctor, and when we play. With the advent of information and communications technology we can collect rich data (video, audio, and various transcripts including text chat) about such interactions. This opens an opportunity to monitor the dynamics of interactions and to get deeper insights of how they unfold and deliver this information to the interacting parties. This paper presents the design of a technology for visualising information about the dynamics of unfolding of interactions and presenting it in an ambient display on mobile devices. The purpose of this technology is the delivery of such information to the point of decision making.

• 영어어문교육
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• 제8권2호
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• pp.219-243
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• 2003

The purpose of the present study was to develop a new English language model of an integrated syllabus for kindergarteners, in order to teach and learn English. An English syllabus is a tool for realizing the goals of a curriculum, in the planning of language teaching that is primarily concerned with content and method components. Thus appropriate syllabus design can play an important role on the whole effectiveness of early English education, because it presents selection and grading of content and method for English textbooks. The basic principle of the present syllabus is based on the national curriculum of kindergartens. Developing an English syllabus model for kindergarteners could suggest standards and directions for teaching and writing adequate English textbooks for kindergarteners. The syllabus model integrates competence in communication using a proportional approach and focussing on the characteristics of kindergarteners. This study presented an integrated English syllabus for kindergarteners at the ages of five, six, and seven.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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• pp.421-423
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• 2007

The paper used to the Neral Netwok for a forecasting conservation system A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. The true power and advantage of neural network lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Netwok is will play an important role for insulation diagnosis system of real site GIS and power equipment using $SF_6$ gas.

• 음성과학
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• 제6권
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• pp.83-101
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• 1999

The aim of this study is to provide a learning method of prosodic rhythm for Taegu North Kyungsang Korean speakers to learn French rhythm more effectively. The rhythmic properties of spoken French and Taegu North Kyungsang Korean dialect are different from each other. Therefore, we try to provide a basic rhythmic model of the two languages by dividing into three parts: syllable, rhythmic unit and accent, and intonation. To do so, we recorded French of Taegu Kyungsang Korean speakers, and then analysed and compared the rhythmic properties of Korean and French by spectrograph. We tried to find rhythmic mistakes in their French pronunciation, and then established a learning model to modify them. After training with the CSL Macro learning model, we observed the output result. However, although learners understand the method we have proposed, an effective method which is possible by repeating practice must be arranged to be actually used in direct verbal communications in a well-developed learning programme. Hence, this study may play an important role at the level of preparation in the setting of an effective rhythmic learning programme.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제15권2호
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• pp.141-158
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• 2011

In recent years, an increasing number of viewpoints hold that students should be engaged in a learning environment where understanding and knowledge transfer take place. This study introduces Mathematics Created by You (MCY)-mentoring program, which allows students to construct artefacts that are required to learn. This program is online-based and so can be shared by several people and mathematics leaning takes place through interactions within this carefully designed environment. Also, MCY intends to provide students a series of sequential activities related to creative play, creative learning and creative inquiry based on a Constructive and interactive environment. Furthermore, a creative activity- constructing a creative product using building blocks- was presented as an example. Finally, we investigate the pedagogical implications and suggest directions for the further development.

• ETRI Journal
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• 제38권6호
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• pp.1229-1239
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• 2016

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

• 한국산업융합학회 논문집
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• 제14권3호
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• pp.95-100
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• 2011

The modern society longing for the convenience of up-to-date technology, there are attempts of miniaturization and high reliance of power equipments in the effectiveness aspect of urban area's usage of space while requiring more electrical energy than now. Consequently, paper used to the Neral Network for a forcasting conservation system. A neral network is powerful asta modeling tool that is able to capture and represent complex input/output relationships. The true power and advantage of neral networks lies in their ability to learn these relationships directly from the data being modeled. Traditional linear models are simply inadequate when it comes to modeling data that contains non-linear characteristics. Form results of this study, the Neral Network is will play an important role for insulation diagnosis system of real site GIS and power eqipment using $SF_6$ gas.

• 한국수학사학회지
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• 제29권5호
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• pp.267-278
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• 2016

Mathematics is a kind of language, and even a tool of cognition for human beings. Mathematics has been used to communicate and to develop the civilizations through the history. So mathematics is one of the most important subjects for human to teach and learn. Especially, developed countries believe that mathematics will play very important roles in the developments of future industries and so future society. In this article, we clarify that combinatorics which is mainly represented by counting is an important ingredient of future mathematics education. To do so, we investigate the characteristics of combinatorics from the educational and cognitive perspectives.

• 스마트미디어저널
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• 제9권3호
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• pp.9-17
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• 2020

Hippocampus is a complex brain structure embedded deep into the temporal lobe. Studies have shown that this structure gets affected by neurological and psychiatric disorders and it is a significant landmark for diagnosing neurodegenerative diseases. Hippocampus features play very significant roles in region-of-interest based analysis for disease diagnosis and prognosis. In this study, we have attempted to learn the embeddings of this important biomarker. As conventional metric learning methods for feature embedding is known to lacking in capturing semantic similarity among the data under study, we have trained deep Siamese convolutional neural network for learning metric of the hippocampus. We have exploited Gwangju Alzheimer's and Related Dementia cohort data set in our study. The input to the network was pairs of three-view patches (TVPs) of size 32 × 32 × 3. The positive samples were taken from the vicinity of a specified landmark for the hippocampus and negative samples were taken from random locations of the brain excluding hippocampi regions. We have achieved 98.72% accuracy in verifying hippocampus TVPs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1428-1429
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• 2007

The paper used to the Neral Netwok for a forecasting conservation system. A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. The true power and advantage of neural network lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Netwok is will play an important role for insulation diagnosis system of real site GIS and power equipment using Dry-Air gas.