• The Journal of the Korea Contents Association
• /
• v.20 no.1
• /
• pp.573-580
• /
• 2020

The purpose of this study was to explore and to suggest the effective teaching methods for university students to improve their speaking abilities through peer assessment-feedback and self assessment-feedback based presentation and debate class. The objects and content of the study were the students who took a class "Reading and Communication" of H university, and here examine closely the speaking activities and their effects during the integrated activities of 'reading, speaking and writing'. In speaking education peer and self assessment feedback is to form an emotional consensus among the students and encourage active participation, and enable self-discovery and communication learning to students. As a result of the study, it was found that the variety speaking practice had a very positive effect on the attitude of speaking and the psychological aspect, and it was confirmed that the evaluation and feedback activities had a meaningful learning effect on the students. Effective speech education and guidance measures should be continuously studied and developed.

• Journal of Educational Research in Mathematics
• /
• v.24 no.3
• /
• pp.359-374
• /
• 2014

Students' difficulties and errors in relation to mathematical proofs are worth while to say one of the dilemmas in mathematics education. The potential elements of their difficulty are scattered over the process of proving in geometry as well as algebra. This study aims to investigate whether middle school students understand the context of algebraic proof including literal expressions. We applied 24 third-grade middle school students a test item which shows a proof including a literal expression and missing the conclusion. Over the half of them responded wrong answers based on only the literal expression without considering its context. Three of them were interviewed individually to show their thinking. As a result, we could find some characteristics of their thinking including the perspective on proof as checking the validity of algebraic expression and the gap between proving and understanding of proof etc. From these, we also discussed about several didactical implications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.2 no.3
• /
• pp.87-95
• /
• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• Convergence Security Journal
• /
• v.18 no.5_1
• /
• pp.45-51
• /
• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• The Mathematical Education
• /
• v.58 no.3
• /
• pp.383-401
• /
• 2019

This study started with the idea that it is necessary to focus on common concepts and ideas among the subjects when conducting integrated education in high school. This is a preliminary study for developing materials that can be taught in mathematics in the context of already learning scientific concepts in high school. For this purpose, Mendel 's law of genetics was studied among the contents of biological subjects which are known to have relatively little connection with mathematics. The more common links between the two subjects are, the better, in order to integrate math and other subjects and develop materials for teaching. Therefore, in this study, we investigated not only the probability domain but also the concept of statistical domain. We have been wondering if there is a more abundant idea to connect between 'Mendel's law' and 'probability and statistics'. Through these anxieties, we could find that concepts such as 'likely equality' and 'permutation and combination' including 'a large number of laws' can be a link between two subjects. Based on this, we were able to develop class materials that correspond to classes. This study is expected to help with research related to development of integrated education support materials, focusing on mathematics.

• Journal of the Korea Convergence Society
• /
• v.10 no.6
• /
• pp.251-257
• /
• 2019

The purpose of this study was to inquire into performance of Wechsler Intelligence Scale for Children based on HOME environment stimuli and age. For the purpose of this, a trained tester carried out K-WISC-IV oriented to 128 children aged 6-16, and this study conducted HOME to mothers. Regarding participants' full Scale IQ and 4 index score(Verbal Comprehension, Perceptual Reasoning, Working Memory, Processing Speed) and HOME, they were analyzed by age group of two: a group of children aged 6-10 and another group of children aged 11-16. According to the analysis results, both age groups showed a significant positive correlation between Full Scale IQ, Verbal Comprehension Index, and HOME environment stimuli. The results of this study were discussed and proposed the necessity of studies in relation to performance of diverse subtests in accordance with amendment of future intelligence scales.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.23-30
• /
• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.731-734
• /
• 2009

In this paper, we propose the method the vehicle color recognizing in the image including a vehicle. In an image, the color feature vector of a vehicle is extracted and by using the backpropagation learning algorithm, that is the multi-layer perceptron, the recognized vehicle color. By using the RGB and HSI color model the feature vector used as the input of the backpropagation learning algorithm is the feature of the color used as the input of the neural network. The color of a vehicle recognizes as the white, the silver color, the black, the red, the yellow, the blue, and the green among the color of the vehicle most very much found out as 7 colors. By using the image including a vehicle for the performance evaluation of the method proposing, the color recognition performance was experimented.

• The Mathematical Education
• /
• v.60 no.1
• /
• pp.1-19
• /
• 2021

This study investigates students' conceptions of fractions from a measurement approach while providing a technological environment designed to support students' understanding of the relationships between quantities and adjustable units. 13 third-graders participated in this study and they were involved in a series of measurement tasks through task-based interviews. The tasks were devised to investigate the relationship between units and quantity through manipulations. Screencasting videos were collected including verbal explanations and manipulations. Drawing upon the theory of semiotic mediation, students' constructed concepts during interviews were coded as mathematical words and visual mediators to identify conceptual profiles using a fine-grained analysis. Two students changed their strategies to solve the tasks were selected as a representative case of the two profiles: from guessing to recursive partitioning; from using random units to making a relation to the given unit. Dragging mathematical objects plays a critical role to mediate and formulate fraction understandings such as unitizing and partitioning. In addition, static and dynamic representations influence the development of unit concepts in measurement situations. The findings will contribute to the field's understanding of how students come to understand the concept of fraction as measure and the role of technology, which result in a theory-driven, empirically-tested set of tasks that can be used to introduce fractions as an alternative way.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.12
• /
• pp.35-44
• /
• 2020

In this study, we analyze how stock trend determination affects trend prediction accuracy. In stock markets, successful investment requires accurate stock price trend prediction. Therefore, a volume of research has been conducted to improve the trend prediction accuracy. For example, information extracted from SNS (social networking service) and news articles by text mining algorithms is used to enhance the prediction accuracy. Moreover, various machine learning algorithms have been utilized. However, stock trend determination has not been properly analyzed, and conventionally used methods have been employed repeatedly. For this reason, we formulate the trend determination as a moving average-based procedure and analyze its impact on stock trend prediction accuracy. The analysis reveals that trend determination makes prediction accuracy vary as much as 47% and that prediction accuracy is proportional to and inversely proportional to reference window size and target window size, respectively.