• Journal of Digital Convergence
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• 제15권1호
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• pp.393-401
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• 2017

This article aims to suggest a principle frame and direction for the development of the character education program using Maumgram. Maumgram is said to clearly illustrate step-by-step structures of character education, for which the human mind is classified as four types(indulged type, rage-type, competition type, selfishness type) on the basis of the existing analytical psychology and Yogacara Thought. The design of the mind type program is composed of three steps. The first step is the 'discovery' step to awaken the cause of self-consciousness through observation, and the second is the 'conversion' step. Learning process to control the negative desires in a positive desire, and the third is the 'relationship'-oriented step to promote a sense of community with other people.

• Journal of the Korea Society of Computer and Information
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• 제23권10호
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• pp.11-21
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• 2018

In this paper we propose a novel log template discovery algorithm which achieves high quality of discovered log templates through iterative log filtering technique. Log templates are the static string pattern of logs that are used to produce actual logs by inserting variable values during runtime. Identifying individual logs into their template category correctly enables us to conduct automated analysis using state-of-the-art machine learning techniques. Our technique looks at the group of logs column-wise and filters the logs that have the value of the highest proportion. We repeat this process per each column until we are left with highly homogeneous set of logs that most likely belong to the same log template category. Then, we determine which column is the static part and which is the variable part by vertically comparing all the logs in the group. This process repeats until we have discovered all the templates from given logs. Also, during this process we discover the custom patterns such as ID formats that are unique to the application. This information helps us quickly identify such strings in the logs as variable parts thereby further increasing the accuracy of the discovered log templates. Existing solutions suffer from log templates being too general or too specific because of the inability to detect custom patterns. Through extensive evaluations we have learned that our proposed method achieves 2 to 20 times better accuracy.

• The Mathematical Education
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• 제43권4호
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• pp.419-440
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• 2004

The purpose of this paper is to know the effects on number and operation abilities of the 1st grade children of elementary school by applying teaching and learning activity throught communication. For this purpose, we have studied according to the following procedure. 1. We divised teaching and learning model through communication and applied in the actual teaching and learning activity. 2. We investigated the effects of number and operations abilities of the 1st grade children by applying teaching and learning activity through communication. To accomplish this purpose, we applied learning activity through communication to the 1st grade of 40 elementary school children for about six months(September 1, 1999 ～ February 20, 2000). In process of applying this model, we collected all sorts of cases in the children's learning activity and investigated children's response on learning activity through communication, interview with children and researcher's observation. We applied the model through communication in class and compared with the traditional learning. 1. In learning through communication, children could solve the problem in themselves with a sense of responsibility. 2. It was impossible to find out the degree of children's comprehension in the explanatory learning. But in the learning through communication, it was a great help to individualize and plan the learning because children express their ideas clearly. It has conclusion as follows. The learning activity through communication has effected on forming number and operations abilities of the 1st grade of elementary school children importantly. 1. Children have improved in the abilities through communication to express their own ideas. 2. Children have studied with a sense of responsibility not in the teacher-oriented learning but in the self-directed learning 3. Children could find out the mathematical concepts in themselves - correcting false concepts, reguiding concepts by errors, finding invisible errors, solving problems variously and knowing the easy method. 4. The activity through communication in mathematics was a base of children's individual learning and important data of next learning plan. 5. The mathematical concepts formed through communication had a high transfer of learning. 6. Children have taken pleasure of discovery and had affirmative attitude about mathematics learning. We can make sure that number and operations abilities of the 1st grade children are formed by applying teaching and learning activity through communication. However, help and control of teacher have to be with it.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.175-178
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• 2005

스마트 홈과 같은 유비쿼터스 환경은 다양한 센서 및 제어 네트워크가 밀집되어 있는 복잡한 시스템이다. 본 논문에서는 이러한 환경하에서 복잡한 인터페이스의 사용에 대한 사용자의 인지 부담(cognitive load)를 줄이고 개인화된(personalized) 서비스를 자율적으로 제공하기 위한 사용자 행동 패턴 선호도 학습 기법을 제안한다. 이를 위해 지식 발견(Knowledge Discovery)을 위한 평생 학습(life-long learning)의 관점에서 퍼지 귀납(Fuzzy Inductive)학습 방법론을 제안하며, 이것은 수치 데이터로부터 입력 공간에 대한 효율적인 퍼지 분할(fuzzy partition)을 얻어내고 일관성있는(consisitent) 퍼지 상관 룰(fuzzy association rule)을 얻어내도록 한다.

• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.305-313
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• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

• Journal of The Korean Astronomical Society
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• 제55권4호
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• pp.131-138
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• 2022

We report the discovery of four quasars with M₁₄₅₀ ≳ -25.0 mag at z ~ 5 and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and Bayesian information criterion, which are expected to be effective in discriminating quasars from the late-type stars and high-redshift galaxies. The candidates were observed by the Double Spectrograph on the Palomar 200-inch Hale Telescope. They show clear Lyα breaks at about 7000-8000 Å, indicating they are quasars at 4.7 < z < 5.6. For HSC J233107-001014, we measure the mass of its supermassive black hole (SMBH) using its C _IV λ1549 emission line. The SMBH mass and Eddington ratio of the quasar are found to be ~10⁸ M_⊙ and ~0.6, respectively. This suggests that this quasar possibly harbors a fast growing SMBH near the Eddington limit despite its faintness (L_Bol < 10⁴⁶ erg s^-1). Our 100% quasar identification rate supports high efficiency of our deep learning and Bayesian information criterion selection method, which can be applied to future surveys to increase high-redshift quasar sample.

• Korean Journal of Materials Research
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• 제33권4호
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• pp.164-174
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• 2023

The bandgap characteristics of semiconductor materials are an important factor when utilizing semiconductor materials for various applications. In this study, based on data provided by AFLOW (Automatic-FLOW for Materials Discovery), the bandgap of a semiconductor material was predicted using only the material's compositional features. The compositional features were generated using the python module of 'Pymatgen' and 'Matminer'. Pearson's correlation coefficients (PCC) between the compositional features were calculated and those with a correlation coefficient value larger than 0.95 were removed in order to avoid overfitting. The bandgap prediction performance was compared using the metrics of R² score and root-mean-squared error. By predicting the bandgap with randomforest and xgboost as representatives of the ensemble algorithm, it was found that xgboost gave better results after cross-validation and hyper-parameter tuning. To investigate the effect of compositional feature selection on the bandgap prediction of the machine learning model, the prediction performance was studied according to the number of features based on feature importance methods. It was found that there were no significant changes in prediction performance beyond the appropriate feature. Furthermore, artificial neural networks were employed to compare the prediction performance by adjusting the number of features guided by the PCC values, resulting in the best R² score of 0.811. By comparing and analyzing the bandgap distribution and prediction performance according to the material group containing specific elements (F, N, Yb, Eu, Zn, B, Si, Ge, Fe Al), various information for material design was obtained.

• Journal of The Korean Association For Science Education
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• 제21권2호
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• pp.357-384
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• 2001

In this paper, we described practical teaching-learning plans based on three different theoretical approaches to Integrated Science Education (ISE): a knowledge centered ISE, a social problem centered ISE, and an individual interest centered ISE. We believe that science teachers can understand integrated science education through this paper and they are able to apply simultaneously our integrated science teaching materials to their real instruction in classroom. For this we developed integrated science teaching-learning plans for the topic of energy which has a integrated feature strongly among integrated science subject contents. These modules were based upon the teaching strategies of 'Energy' following each integrated directions organized in the previous paper (Three Strategies for Integrated Science Teaching of "Energy" Applying Knowledge, Social Problem, and Individual Interest Centered Approaches) and we applied instruction models fitting each features of integrated directions to the teaching strategies of 'Energy'. There is a concrete describing on the above three integrated science teaching-learning plans as follows. 1. For the knowledge centered integration, we selected the topic, 'Journey of Energy' and we tried to integrate the knowledge of physics, chemistry, biology, and earth science applying the instruction model of 'Free Discovery Learning' which is emphasized on concepts and inquiry. 2. For the social problem centered integration, we selected the topic, 'Future of Energy' to resolve the science-related social problems and we applied the instruction model of 'Project Learning' which is emphasized on learner's cognitive process to the topic. 3. For the individual interest centered integration, we selected the topic, 'Transformation of Energy' for the integration of science and individual interest and we applied the instruction model of 'Project Learning' centering learner's interest and concern. Based upon the above direction, we developed the integrated science teaching-learning plans as following steps. First, we organized 'Integrated Teaching-Learning Contents' according to the topics. Second, based upon the above organization, we designed 'Instructional procedures' to integrate within the topics. Third, in accordance with the above 'Instructional Procedures', we created 'Instructional Coaching Plan' that can be applied in the practical world of real classrooms. These plans can be used as models for the further development of integrated science instruction for teacher preparation, textbook development, and classroom learning.

• Journal of The Korean Association of Information Education
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• 제8권4호
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• pp.537-545
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• 2004

In spite of the fact that project-based learning has had positive effects on improvement of creation power and expansion of the spirit of inquiry, the project-based learning lesson was difficult to carry out in the classroom. The web overcomes time and space limitations in traditional schools. This study has developed and implemented an online project-based website of children's education, based upon the extensive classroom use of multimedia materials to further students participation and interest in projects of discovery. The developed website shows the entire process used through out the project. This paper presents the project's activities and students' learning, using multimedia and web. This study was conducted in fourth grade of an elementary school for a month. The results of this study suggest that the effects of using the project-based website were improved self-directed learning and generation of new ideas.

• Journal of The Korean Association of Information Education
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• 제23권6호
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• pp.639-653
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• 2019

The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.