• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.869-876
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• 2021

In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.138-147
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• 2022

Recently, chatbots have been applied in various fields and have shown good results, and many attempts to use chatbots in shopping mall product recommendation services are being conducted on e-commerce platforms. In this paper, for a conversation system that recommends a fashion that a user wants based on conversation between the user and the system and fashion image information, a transformer model that is currently performing well in various AI fields such as natural language processing, voice recognition, and image recognition. We propose a multimodal-based improved transformer model that is improved to increase the accuracy of recommendation by using dialogue (text) and fashion (image) information together for data preprocessing and data representation. We also propose a method to improve accuracy through data improvement by analyzing the data. The proposed system has a recommendation accuracy score of 0.6563 WKT (Weighted Kendall's tau), which significantly improved the existing system's 0.3372 WKT by 0.3191 WKT or more.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.647-660
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• 2022

Recent works demonstrate that the semi-supervised anomaly detection method functions quite well in the environment with normal data and some anomalous data. However, abnormal data shortages can occur in an environment where it is difficult to reserve anomalous data, such as an unknown attack in the cyber security fields. In this paper, we propose ADA-PH(Abnormal Data Augmentation Method using Perturbation based on Hypersphere), a novel anomalous data augmentation method that is applicable in an environment where abnormal data is insufficient to secure the performance of the semi-supervised anomaly detection method. ADA-PH generates abnormal data by perturbing samples located relatively far from the center of the hypersphere. With the network intrusion detection datasets where abnormal data is rare, ADA-PH shows 23.63% higher AUC performance than anomaly detection without data augmentation and even performs better than the other augmentation methods. Also, we further conduct quantitative and qualitative analysis on whether generated abnormal data is anomalous.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.91-97
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• 2021

This paper uses a data extension technique originally designed for the rule refinement problem to handling incomplete data. This technique is characterized in that each event can have a weight indicating importance, and each variable can be expressed as a probability value. Since the key problem in this paper is to find the probability that is closest to the missing value and replace the missing value with the probability, three different algorithms are used to find the probability for the missing value and then store it in this data structure format. And, after learning to classify each information area with the SVM classification algorithm for evaluation of each probability structure, it compares with the original information and measures how much they match each other. The three algorithms for the imputation probability of the missing value use the same data structure, but have different characteristics in the approach method, so it is expected that it can be used for various purposes depending on the application field.

• Journal of the Korean Chemical Society
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• v.67 no.4
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• pp.241-252
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• 2023

This study aims to increase students' understanding of equilibrium, one of the many concepts in chemistry that students find difficult. Dynamic equilibrium must be dealt with at the sub-microscopic level where the real and the representation overlap in order to microscopically understand the constant motion and interaction of particles and to understand the macroscopic characteristics expressed through this. However, as a result of analyzing 9 Chemistry I textbooks, the expression approach for equilibrium had some limitations. As a strategy to understand equilibrium at a sub-microscopic approach, the classes using scratch were consisted of a total of 4 hours, and it was implemented with 56 students. The classes were composed of 6 steps, and it was designed to understand equilibrium step by step. As a result of comparing the pretest and post- test, the number of students who got both the microscopic and macroscopic explanations of chemical equilibrium correct increased largely. Through this, it was possible to get a glimpse of the applicability of classes using scratch as the approach strategy of the sub-microscopic representation.

• 한국체육학회지인문사회과학편
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• v.51 no.4
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• pp.23-31
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• 2012

The purpose of this study was to inquiry implication of physical education based on the Zhaung Zi's philosophy. In order to investigate this purpose, I analyzed the text of Zhaung Zi. The result of the study was as followed. Zhaung-Zi oriented ideal image of human beings who has attained the stage of play(遊). He is an acquaintance (至仁), a man of god(神人), a true man(眞人). The purpose of physical education in Zhuang-Zi is paly(遊) which play well naturally. 'play is the gaming and play in which we can see the true face of the world and ourselves and can become on with the object in the world. Forget-enjoyment(至樂) of victory, records, and results are the purpose of physical education which can be found in Zhuang-Zi. The methods of physical education is the whole mind(專一), xixium(虛心), the feast of mind(心齋), forgetting everything(坐忘) etc. Physical education is to harmonious study with nature not artificially. The relation between teacher(coach) and student(player) is a relationship of mutual respect and consideration. The teacher(player) have to find the potential ability of student and he can help student realize potential ability of them.

• Smart Media Journal
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• v.11 no.2
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• pp.18-24
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• 2022

Problems caused by malicious comments occur on many social media. In particular, YouTube, which has a strong character as a medium, is getting more and more harmful from malicious comments due to its easy accessibility using mobile devices. In this paper, we designed and implemented a YouTube malicious comment detection system to identify malicious comments in YouTube contents through LSTM-based natural language processing and to visually display the percentage of malicious comments, such commentors' nicknames and their frequency, and we evaluated the performance of the system. By using a dataset of about 50,000 comments, malicious comments could be detected with an accuracy of about 92%. Therefore, it is expected that this system can solve the social problems caused by malicious comments that many YouTubers faced by automatically generating malicious comments statistics.

• Korean Educational Research Journal
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• v.43 no.1
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• pp.183-213
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• 2022

The purpose of this study is to examine the implications of Deleuze and Guattari's Machinism and Pedagogy of Assemblages. A slow, empirical process offered by Deleuze and Guattari is possible only if they experience a repetition of the duration in time. The identity of this world, a combination of potential and reality, is expressed as a machine. The identity of the 'machine' is the generation. The identity of the information society that exists everywhere in the cloud and unconsciously collects big data is also the information society. The information society is at risk of leaning toward a society in which individual desires are managed prior to the manifestation of a self-reliance a machine consisting of unmarked and mechanical arrangements. Social science based on the theory of layout shares the characteristics of repetition patterns, coexistence of linguistic and materiality, attention to boundary and negation to total whole. The pedagogy of layout, in which the collective pattern is structurally deformed in time, conforms to the original problem consciousness of Deleuze and Guattari, slow and empirical education. In addition, the work of examining the materiality and expression of the education-machine will contribute to the establishment of a new learning theory, an educational theory in the era of trans-human.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.151-154
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• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.326-327
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• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.