• Journal of The Korean Association For Science Education
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• v.24 no.2
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• pp.246-257
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• 2004

The purpose of this qualitative study was to identify high school students' conceptual differentiation patterns on human digestion system. The subjects were 124 high school students and this group was guided to independently construct concept maps. Among them, 19 were selected for an in-depth interview and a short test. The concept maps, interview transcripts and the results of short-test were analyzed to identify conceptual differentiation patterns. The results were as follows. Mainly three distinct conceptual differentiation patterns were identified. The first pattern can be named as an 'Free-flow type'. The group belongs to this pattern expressed numerous examples than meaningful concepts with unclear understanding of hierarchial relation between each concepts. Also, this group had difficulties in grasp interrelations of different concepts. The second pattern can be identified as 'Sequence type'. This group constructed concept maps by featuring conceptual sequence. The group applied meaningful learning, yet assembled concept maps primarily according to sequence of learning and exhibited less organized concept maps than hierarchial type. The third pattern can be named as 'Hierarchial type'. All students elaborated concept maps after lessons. The sequence type changed hierarchial type or sequence mixed with hierarchial type but free-flow type was hardly changed.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.395-408
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• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.135-140
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• 2012

The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

• Journal of Korean Classical Literature and Education
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• no.34
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• pp.75-113
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• 2017

The purpose of fusion education is to acquire educational contents efficiently and gain a new worldview. To realize this purpose, I point out that it is urgent to provide common educational content and suggest "place experience" as common content for literature and geography. Local legends present a concrete space and a sharp confrontation with the human world, while shaping the tradition of a place's name. Place experience as common educational content enables a three-dimensional experience of a place that utilizes the characteristics of these local legends. The physical condition, human activity, and implied meaning of a place mediate the student's empirical understanding of folktales. The common area of "place experience" allows us to expect a stereotypical understanding of a learner's place by providing a literary context to learning contents that can flow from the existing geography subject to the simple provision of information. In addition, it facilitates learners' empirical understanding by providing actual and specific objects to learning contents, which can flow abstractly in the existing literature subject. Through this discussion, convergence education demonstrates educational significance by achieving educational efficiency through common educational content and enabling the formation of new thinking.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• (The) Research of the performance art and culture
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• no.37
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• pp.365-389
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• 2018

This research aims to study Michael Chekhov's acting techniques scientifically, because his techniques has been studied only theoretically or empirically. Especially, this study focuses on 'imagination' and 'Psychological Gesture' from the perspective of cognitive psychology. Chekhov thought 'imagination' as the basis and core of all the works of acting. In cognitive psychology, it is called as 'imagery' and means 'a representation of the mind of the object not communicated by the sensory organs currently'. This study starts with defining imagery and takes a brief look at the features and kinds of imagery. Then the researcher will prove scientifically the possibility of training acting using imagery as Chekhov's assertion. For the proof of the validity of imagery, we'll look for the theoretical evidences-functional equivalence hypothesis, psychoneuromuscular theory, symbolic learning theory, psychophygiological information processing-and experimental ones-measurements of cerebral blood flow or event-related potential, experiments with fMRI(functional magnetic resonance imaging) or PET(positron emission tomography). As a result, we can see that imagery is functionally identical to perception and improves fulfillment of cognitive and physical tasks. As proving physical changes can draw out psychological changes(feeling) on the medium of imagery, we can also see the validity of Psychological Gesture. From the above research, even if Chekhov developed the acting techniques only on the basis of his experience, his techniques can be thought as having scientific validity. Though insufficient, this study can be a help for actors or students as they using Chekhov's techniques.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.

• Journal of KIISE:Information Networking
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• v.33 no.3
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• pp.201-217
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• 2006

In this paper, we collected the physical traces from high speed Internet backbone traffic and analyze the various characteristics of the underlying packet traces. Particularly, our work is focused on analyzing the characteristics of an anomalous traffic. It is found that in our data, the anomalous traffic is caused by UDP session traffic and we determined that it was one of the Denial of Service attacks. In this work, we adopted the unsupervised machine learning algorithm to classify the network flows. We apply the k-means clustering algorithm to train the learner. Via the Cramer-Yon-Misses test, we confirmed that the proposed classification method which is able to detect anomalous traffic within 1 second can accurately predict the class of a flow and can be effectively used in determining the anomalous flows.

• Journal of Korean Elementary Science Education
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• v.35 no.2
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• pp.205-215
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• 2016

This study aims to investigate how elementary teachers use teachers' guide in preparation for science lessons. First, different uses of teacher's guide were analyzed. Second, how and why teachers use each section in teacher's guide were analyzed. For the study, 24 elementary school teachers were interviewed in depth. The semi-structured in-depth interviews were conducted individually and/or in small group, and additional interviews were held when necessary. The results showed that most of the teachers used teacher's guide only substitutionally, and some teachers rarely use teacher's guide, while only 3 out of 24 teachers used teacher's guide in detail. The reasons that teachers used the teacher's guide substitutionally or rarely were that most science lessons include experiments, and science textbook itself provides enough information for preparation of science lessons for 3rd and 4th grade students. The results also revealed that only few teachers read the general guideline in teacher's guide. Some sections of teacher's guide were not used. The sections that many teachers used were the aims of lesson, the learning system of the unit, background knowledge, flow of lesson, learning contents and activities. This study specifically examined the actual use of teacher's guide for lesson preparation and discussed implications for the development of more helpful teacher's guide.

• Journal of The Korean Association of Information Education
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• v.6 no.2
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• pp.234-245
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• 2002

A new era has come where high quality educational materials can be acquired easily through the World Wide Web. These materials, however, need to be refined and streamlined to maximize their effect on education. In order to provide such a streamlined flow, we need to be able to re-organize documents, which exist independent of each other on the Web, in a way that maintains their appropriate order in the right context to satisfy educational purposes. In addition, we should be able to provide supplementary explanations or missing information to the organized materials for smooth connections among them. In order to meet the requirements, we employed the virtual document concept that allows us to reuse existing documents for educational purposes. By providing a retrieval engine for virtual documents, we attempt to induce self-directed learning based on document retrieval, suitable for the level and purpose of students.