• Journal of Industrial Convergence
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• v.18 no.1
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• pp.53-58
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• 2020

The 2015 revised curriculum aims to cultivate creative convergence talent. In this regard, SW education needs to study various convergence education methods to enhance computational thinking. The purpose of this study is to analyze the effects of SW convergence education centered on reading education and robot utilization education to improve computing thinking ability. For this purpose, SW education teaching and learning was designed by combining SW education using card coding-based robots with reading education based on interactive works and reading on the whole work. As a result, the convergence education between reading and SW improved all three areas of the concept, practice, and perspective of computational thinking ability and increased the learner's satisfaction.

• Journal of Korean Elementary Science Education
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• v.27 no.2
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• pp.158-169
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• 2008

The purpose of this study was to analyze the uses of the external representations in the $3{\sim}6th$ grade science textbooks developed under the 7th National Curriculum on the basis of the theories and the research results on learning with the multiple representations. The results showed that the frequencies of the macroscopic external representations were higher than those of the symbolic external representations. The external representations with drawing and/or writing, especially writing, were used more frequently than those without drawing and/or writing. However, the most of the external representations were rarely used according to the principles and/or the theories (e.g., personalization principle, dual coding theory, cognitive load theory, and social constructivism theory) for effective uses of the multiple external representations in the science textbooks. The present study provides the guideline to establish the effective uses of the external representations in the science textbooks that not only meet learners but also teachers.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.695-705
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• 2019

The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

• ETRI Journal
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• v.41 no.4
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• pp.415-425
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• 2019

Generative adversarial networks (GAN) have been successfully used in many image restoration tasks, including image denoising, super-resolution, and compression artifact reduction. By fully exploiting its characteristics, state-of-the-art image restoration techniques can be used to generate images with photorealistic details. However, there are many applications that require faithful rather than visually appealing image reconstruction, such as medical imaging, surveillance, and video coding. We found that previous GAN-training methods that used a loss function in the form of a weighted sum of fidelity and adversarial loss fails to reduce fidelity loss. This results in non-negligible degradation of the objective image quality, including peak signal-to-noise ratio. Our approach is to alternate between fidelity and adversarial loss in a way that the minimization of adversarial loss does not deteriorate the fidelity. Experimental results on compression-artifact reduction and super-resolution tasks show that the proposed method can perform faithful and photorealistic image restoration.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.420-429
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• 2019

Recently, researches using Convolutional Neural Network (CNN)-based approaches have been actively conducted to improve the reduced quality of compressed video using block-based video coding standards such as H.265/HEVC. This paper aims to summarize and analyze the network models in these quality enhancement studies. At first the detailed components of CNN for quality enhancement are overviewed and then we summarize prior studies in the image domain. Next, related studies are summarized in three aspects of network structure, dataset, and training methods, and present representative models implementation and experimental results for performance comparison.

• Clinical and Experimental Reproductive Medicine
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• v.49 no.4
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• pp.225-238
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• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

• The Journal of Korean Association of Computer Education
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• v.11 no.1
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• pp.57-64
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• 2008

This paper presents a web-based virtual educational system for Java language, which consists of a management system named Java Web Player (JWP) and creative multimedia contents for the lectures of Java language. The JWP is a Java application program free from security problems by the Java Web Start technologies that supports an integrated learning environment including three important learning procedures: Java concept learning process, programming practice process and assessment process. On-line voice presentation and its related texts together with moving images are synchronized for efficiently conveying creative contents to learners. Furthermore, a simple and useful compiler is included in the JWP for providing user-friendly language practice environment enabling such as coding, editing, executing, and debugging Java source files on the Web. Finally, simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box. In order to show the validity of the proposed virtual educational system we analysed and assessed the learners' academic performance on the five quizzes for one semester.

• Journal of Elementary Mathematics Education in Korea
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• v.13 no.1
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• pp.75-95
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• 2009

The purpose of the study was to investigate the scaffolding processes of children in mathematical problem solving. 3 groups of 4th grade students participated in the study and the researchers proceeded the study for 4 months. The procedures of this research were as followings. First, when the learners solved the problems, the categories of scaffolding processes(by way of unit line coding belong in open codings, the categories were made 25 concepts and integrated 20 subcategories) were produced the 7 results: invite to the learning, set the problems, affective aids, attempt self learning, re-ordering between learners and affirmation self learning. Second, the processes of scaffolding in mathematic problem solving resulted in condition, the present condition, action/interaction and the outcomes. Third, the cognitive and affective aids that discovered in the scaffolding processes were considered the main categories of learner's scaffolding processes in solving the mathematic problems. In conclusion, first, the learners' scaffolding processes, based on Vygotsky's "the zone of proximal development" in selection and presentation of mathematic problems, are very diverse. Peers' affective aids are very important in solving the problems. Second, learners in the scaffolding processes exchange the cognitive and affective aids with each other with joy and earnestness, and the aids can give assistance to all the participants. Third, in the results of observation and analysis in learners' scaffolding processes, it is meaningful to know how they think. Finally, the learners' scaffolding processes are a little unsystematic and illogical compared to those of adults, but those of scaffolders are so similar to those of learners' cognitive and affective systems that they can provide teachers with many merits in understanding and teaching learners.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1131-1139
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• 2020

The static analysis of the source code is to find the remaining security weaknesses for a wide range of source codes. The static analysis tool is used to check the result, and the static analysis expert performs spying and false detection analysis on the result. In this process, the amount of analysis is large and the rate of false positives is high, so a lot of time and effort is required, and a method of efficient analysis is required. In addition, it is rare for experts to analyze only the source code of the line where the defect occurred when performing positive/false detection analysis. Depending on the type of defect, the surrounding source code is analyzed together and the final analysis result is delivered. In order to solve the difficulty of experts discriminating positive and false positives using these static analysis tools, this paper proposes a method of determining whether or not the security weakness found by the static analysis tools is a spy detection through artificial intelligence rather than an expert. In addition, the optimal size was confirmed through an experiment to see how the size of the training data (source code around the defects) used for such machine learning affects the performance. This result is expected to help the static analysis expert's job of classifying positive and false positives after static analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.