• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.313-332
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• 2020

The purpose of this study is to compare motivations for self-archiving across disciplines on an academic social networking site. We carried out an online survey with ResearchGate(RG) users, testing 18 motivational factors that we developed from a previous study (enjoyment, personal/professional gain, reputation, learning, self-efficacy, altruism, reciprocity, trust, community interest, social engagement, publicity, accessibility, self-archiving culture, influence of external actors, credibility, system stability, copyright concerns, additional time, and effort). We adapted Biglan's classification system of academic disciplines and compared motivations across different categories of discipline. First, we compared motivations across the four combined categories by the two dimensions - hard-pure, hard-applied, soft-pure, and soft-applied. We also performed a motivation comparison across each dimension between soft and hard disciplines and between pure and applied disciplines. We examined investigated statistical differences in motivations by demographic characteristics and RG usage of participants across categories as well. Findings showed that there were differences of motivations, such as enjoyment, accessibility, influence of external actors and additional time and effort, and personal/professional gains, for self-archiving across disciplines. For example, RG users in the hard-applied were more highly motivated by enjoyment than others; RG users in the soft-pure were more highly motivated by personal/professional gains than others. It is expected that findings could be used to develop strategies encouraging researchers in various disciplines contributing to share their data and publications in ASNSs.

• Journal of the Korean earth science society
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• v.21 no.4
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• pp.359-368
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• 2000

The purpose of this study is to develope and apply NIE programs related to sub-chapter 'The Change of Weather and Circulation of Water' in 2nd grade science text book of middle school, and thereby to investigate the effects of NIE approach on science-related attitude and teaming achievement of students, and interaction between treatment methods and students' learning ability. Subjects consisted of 2nd grade students of four classes in a girls middle school located at the southern part of Seoul. Four classes were divided into experimental and control groups by two classes randomly. The experimental groups have been instructed on the related-general concepts for six times and then received seven NIE programs developed by researcher for seven times. The control groups have received the instruction through the conventional teaching method. The NIE learning has been progressed following the steps using in the Iowa Chautaugua Program, e.g. invite, explore, propose explanation and solutions, and take action. NIE programs, e.g. project studying, topic studying and a crossword puzzle have been developed and applied using 'science first' approach of the STS instruction. Twenty questions related to social implications of science and leisure interest in science within seven frameworks of TOSRA have been used in this study as an evaluation instrument of science-related attitude. Learning achievement has been evaluated using an instrument developed by researcher. The results of this study can be summarized as follows. (1) NIE approach was more effective in progressing learning achievement of middle school students than conventional teaching method (p<.01). (2) Experimental groups show statistically significant improvement on science-related attitude than control groups (p<.01). There were no significant interactions between treatment methods and students' learning ability on learning achievement and leisure interest in science. The NIE approach were more effective than the conventional one on social implications of science, especially to low ability students.

• The Journal of Korean Association of Computer Education
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• v.20 no.1
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• pp.13-26
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• 2017

The programming(algorithm) automated assessment system is to evaluate automatically the accuracy and time/space efficiency of user's solution to the problem which is provided. This system gives the immediate feedback of the solution, real-time ranking. So, in the course of data structure and algorithm, we can apply the knowledge which we have learned to the problem solving. Especially, in the basic course of learning the syntax of the programming language, the novice student can learn in easy and fun by solving the simple problem. The university students can understand in the easy way the meaning of asymptotic analysis of algorithm in data structure & algorithm course.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.316-321
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• 2017

We analyze the online Hangul handwriting recognition problem (HHR) and present solutions based on recurrent neural networks. The solutions are organized according to the three kinds of sequence labeling problem - sequence classifications, segment classification, and temporal classification, with additional consideration of the structural constitution of Hangul characters. We present a stacked gated recurrent unit (GRU) based model as the natural HHR solution in the sequence classification level. The proposed model shows 86.2% accuracy for recognizing 2350 Hangul characters and 98.2% accuracy for recognizing the six types of Hangul characters. We show that the type recognizing model successfully follows the type change as strokes are sequentially written. These results show the potential for RNN models to learn high-level structural information from sequential data.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.474-481
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• 2013

The purpose of this study is that pre-service teacher are able to design creative instruction based on NFTM-TRIZ for building up their continuous creative thinking and promoting their creative instruction activities. NFTM-TRIZ is a educational technology system to form and develop creative thinking from child to adult continuously based on TRIZ theory. TRIZ is the thinking technique of creative problem solving that can be the tool of inventory solutions by finding and get over the key of contradiction that is necessary to obtain ideal final results of suggested problems. The subjects for this study were 90 pre-service teachers who are attending third and fourth graders of Teachers' College in G university and are taking 'Curriculum and Educational Evaluation'. The creativity program for this study was carried out for ten minutes at the end of lectures. The verification for this study results were performed two faces. First, pre-service teachers presented teaching and learning plan for one time used 8 Steps' Teaching and Learning Model based on NFTM-TRIZ. Second, researcher got feedback from them about this creative program.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1447-1451
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• 2008

저수지 군 연계 운영을 위한 각 댐에서의 방류량을 결정하기 위해서는 대개 각 댐의 초기 저수량, 유역 상 하류 댐의 총 저수량, 수요량, 기간별 발전 목표 달성 정도, 그리고 예상되는 미래유입량 등이 추정되어야 한다. 본 연구에서는 댐 군 연계운영을 위한 일별 최적화 모형인 CoMOM(Coordinated Multi-reservoir Operating Model, 4.2)의 상위 단계의 더 큰 단위 기간에 활용될 댐 군 연계 운영 기본 가이드라인을 신경망 기법을 활용하여 도출할 수 있을 지를 실험해 보고자 한다. 이 방법은 기본적으로 CoMOM이 제시하는 일별 운영 계획의 결과가 최선의 정책일것이라는 가정에 근거하고 있다. 즉, 주어진 상황에서 일별 CoMOM이 제시하는 결과를 교사 신호로 하여 신경망 학습을 수행하고, 이 결과를 통해 규칙(Rule)을 생성하는 과정으로 요약할 수 있다. 신경망 분석은 CoMOM이 이수기 모형인 점을 고려하여 이수기만을 대상으로 실험하였으며, 단위 분석기간을 10일로 택하여 미래 10일간의 방류량을 결정하는 것을 목표로 하였다. 신경망 모형의 입력요소로는 각 댐의 초기 유효 저수량, 유역 상 하류 댐의 총 저수량, 10일간의 수요량, 그리고 향후 한달 동안의 예상 유입량을 적용하였고, 출력요소로는 CoMOM에서 제시한 방류량 결과를 사용하였다. 모형의 유효성을 검증하기 위해 한강수계의 이수기를 대상으로 과거의 유입량 자료가 재현된다고 가정하고, 모의운영을 통하여 적합성을 분석하였다. 이를 위해 매일 단위의 실제 댐 군 연계 운영의 상황을 모의할 수 있는 실시간 시뮬레이션을 적용하였으며, 신경망 모형의 운영 기준에 의해 결정된 향후 10일 동안의 총 방류량이 해당기간 동안 동일한 양으로 나누어 방류된다는 가정 하에 모의 운영하였다. 그리고 도출된 운영 결과는 최종적으로 실적과의 평균저수량, 발전량, 여수로 방류량 비교를 통해 평가하였다.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• Journal of The Korean Association For Science Education
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• v.32 no.2
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• pp.346-371
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• 2012

The purpose of this study is to investigate the possibilities of science ethics education with history of science (HOS) and to develop its teaching and learning model for secondary school students. A total of 72 cases about science ethics were extracted from 20 or more HOS books, journal articles, and newspaper articles. These cases were categorized into 8 areas, such as forgery, fabrication, violation of bioethics in testing, plagiarism and stealth, unfair allocation of credit, over slander, conjunction with ideologies, and social responsibility problems. The results of this study are as follows. First, research forgery, occurring in the process of the research, was the most frequent in HOS. Second, we developed eight teaching lesson plans for each area. Third, we proposed a teaching and learning model based on the developed lesson plans as well as related teaching and learning models in the fields of science ethics education, ethics education, and history education. Our model has five steps, 'investigating-suggesting casesclarifying problems-finding alternatives-summarizing'.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.145-152
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• 2012

Due to the large sizes of streaming media, previous delivery techniques are not providing optimal performance. For this purpose, video proxy server is employed for reducing the bandwidth consumption, network congestion, and network traffic. This paper proposes a fast distributed network file system using state transition model in the media streaming system for efficient utilization of video proxy server. The proposed method is composed of three steps: step 1. Training process using state transition model, step 2. base and decision probability generation, and step 3. storing and deletion based on probability. In addition, storage space of video proxy server is divided into each segment area in order to store the segments efficiently and to avoid the fragmentation. The simulation results show that the proposed method performs better than other methods in terms of hit rate and number of deletion. Therefore, the proposed method provides the lowest user start-up latency and the highest bandwidth saving significantly.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.441-447
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• 2018

This study aims to develop digital techniques that enable repeated practice of dental radiography using augmented reality technology. A three-dimensional object was fabricated by superimposing a photograph of an adult model and a computed tomography image of a manikin phantom. The system was structured using 106 radiographs such that one of these saved radiographs is opened when the user attempts to take a radiograph on a mobile device. This system enabled users to repeatedly practice at the pre-clinical stage without exposure to radiation. We attempt to contribute to enhancing dental hygienists' competency in dental radiography using these techniques. However, a system that enables the user to actually take a radiograph based on face recognition would be more useful in terms of practice, so additional studies are needed on the topic.