• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.23-28
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• 2015

Teaching programming skills is not only required for computer related departments but through the area of engineering and natural science. Moreover recently teaching programming skill is emphasized in software education for primary schools and secondary schools. Since programming ability is considered an essencial element of national competitiveness, we need programming learning system which alleviates the difficulty. We implemented Blockly webc Programming Convergent Learning System which is based on the graphic tools called Blockly by Google. Inside system problem sets for the programming beginners are embedded in the system. These problem sets are gone under more than 20 years verification and these problem sets may be used to help beginning programmers escape novice coder in short time. Blockly webc Programming Convergent Learning System together with already developed Simple Visual Language2 Programming Learning System is expected to play an important role as a programming learning system for the beginners.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.197-207
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• 2022

In this paper, we develop a machine learning based block code generation and recommendation model for the purpose of reducing cognitive load of learners during coding education that learns the learner's block that has been made in the block programming environment using natural processing model and fine-tuning and then generates and recommends the selectable blocks for the next step. To develop the model, the training dataset was produced by pre-processing 50 block codes that were on the popular block programming language web site 'Entry'. Also, after dividing the pre-processed blocks into training dataset, verification dataset and test dataset, we developed a model that generates block codes based on LSTM, Seq2Seq, and GPT-2 model. In the results of the performance evaluation of the developed model, GPT-2 showed a higher performance than the LSTM and Seq2Seq model in the BLEU and ROUGE scores which measure sentence similarity. The data results generated through the GPT-2 model, show that the performance was relatively similar in the BLEU and ROUGE scores except for the case where the number of blocks was 1 or 17.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.193-200
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• 2023

Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.39-46
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• 2018

Departure Manager (DMAN) is a tool to optimize the departure sequence and to suggest appropriate take-off time and off-block time of each departure aircraft to the air traffic controllers. To that end, Variable Taxi Time (VTT), which is time duration of the aircraft from the stand to the runway, should be estimated. In this paper, a study for development of VTT prediction algorithm based on machine learning techniques is presented. The factors affecting aircraft taxi speeds were identified through the analysis of historical traffic data on the airport surface. The prediction model suggested in this study consists of several sub-models that reflect different types of surface maneuvers based on the analysis result. The prediction performance of the proposed method was evaluated using the actual operational data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.239-243
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• 2003

Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.99-100
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• 2018

컴퓨팅 사고력이 강조됨에 따라 우리 나라를 비롯한 세계 여러 나라에서는 프로그래밍 교육 등 컴퓨팅 관련 교육을 실시하고 있다. 일반적으로 프로그래밍 교육에서 초보 학습자에게는 블록 기반 프로그래밍 언어를 학습한 후 텍스트 기반 프로그래밍 언어를 학습하게 된다. 블록 기반 언어와 텍스트 기반 언어는 동일한 프로그래밍 논리를 함양하게 되지만, 다른 모든 언어들과 마찬가지로 언어 특성, 사용법, 형태 등 다소 차이가 있다. 따라서 본 논문에서는 블록 기반 프로그래밍 언어에서 텍스트 기반 프로그래밍 언어의 학습 전이의 효과에 대해 이론적 고찰을 실시하였으며, 그 결과 대부분의 연구에서 긍정적 전이 효과를 입증하였음을 확인하였다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.265-271
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• 2015

This study proposes an algorithm for recognizing apple trees in images and detecting apples to measure the number of apples on the trees. The proposed algorithm explores whether there are apple trees or not based on the number of image block-unit edges, and then it detects apple areas. In order to extract colors appropriate for apple areas, the CIE $L^*a^*b^*$ color space is used. In order to extract apple characteristics strong against illumination changes, modified census transform (MCT) is used. Then, using the AdaBoost learning algorithm, characteristics data on the apples are learned and generated. With the generated data, the detection of apple areas is made. The proposed algorithm has a higher detection rate than existing pixel-based image processing algorithms and minimizes false detection.

• Smart Media Journal
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• v.5 no.2
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• pp.24-32
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• 2016

Recently, the development of electronic teaching materials and the demand of digital learners have led the needs on the education contents that replace learning from character information and the change of an information design method for this. Chinese character education in the traditional schooling mainly focuses on writing and memorization (semantic memory). This way that the stories do not exist has brought the learners' recognition that Chinese character is difficult to learn. Meanwhile, for a language study such as English, cross-media development between printed materials and audio-visual materials has been actively introduced. The method that extends episode memories along with memorization through a story is widely used. Therefore, this content suggests a prototype, which is broken away from an existing way of learning Chinese character that mainly focuses on writing, one sided instruction and information cramming. This makes learners learn through a story from printed materials and animation. Furthermore, it suggests a method that extends episode memories through Chinese education contents based on IoT explaining the principle of Chinese character by combining IT technology (information and communications, IoT) and education contents on block toys.

• Journal of Chest Surgery
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• v.18 no.4
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• pp.598-604
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• 1985

One hundred consecutive patients with the Tetralogy of Fallot underwent total correction at National Medical Center during the period 1977 to 1984, Oct. During this study period, we adopted more active policy towards reconstruction of right ventricular outflow tract across pulmonary valve. The mortality was 48% for patients less than 15 kg and 19% in patients above 15kg. Initially Bretschneider`s solution was used as cardioplegia, which was replaced by St. Thomas` solution since 1983, Jan. After then overall mortality dropped to 9% compared to 45% of initial learning period. Heart block occurred In 11 patients, 10 of whom died of combined low cardiac output syndrome. Pure low cardiac output syndrome was noted in 18 patients, most of whom responded to medical measures well except 4 patients. Recently sepsis of Serratia marcescence, which occurred explosively during several months to open heart surgery patients, attacked 3 tetralogy patients resulting in 2 hospital deaths. Our experience has shown that body weight, choice of cardioplegia and accumulation of experience as well as advance of operative and postoperative techniques are still important factors affecting survival rate at initial learning period.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.635-637
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• 2016

The purpose of this study was to apply other programming tools such as robots parish. The robot was utilized for Lego Mindstorms NXT. Programming tools were used to block generic programming tools were used in the NXT-G, was used as a simulation programming tools MSRDS, mobile App Inventor is a programming tool (App Inventor). It can lead to interesting effects of learning and learning based on three programming tool above.