• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.315-320
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• 2014

Composition is a creative activity of a composer in order to express his or her emotion into melody based on their experience. However, it is very hard to implement an automatic composition program whose composition process is the same as the composer. On the basis that the creative activity is possible from the imitation we propose a method to implement an automatic composition system using the learning capability of ANN(Artificial Neural Networks). First, we devise a method to convert a melody into time series that ANN can train and then another method to learn the repeated melody with melody bar for correct training of ANN. After training of the time series to ANN, we feed a new time series into the ANN, then the ANN produces a full new time series which is converted a new melody. But post processing is necessary because the produced melody does not fit to the tempo and harmony of music theory. In this paper, we applied a tempo post processing using tempo post processing program, but the harmony post processing is done by human because it is difficult to implement. We will realize the harmony post processing program as a further work.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.234-240
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• 2021

In this paper, the mask-based speech enhancement is improved for effective speech recognition in noise environments. In the mask-based speech enhancement, enhanced spectrum is obtained by multiplying the noisy speech spectrum by the mask. The VoiceFilter (VF) model is used as the mask estimation, and the Spectrogram Inpainting (SI) technique is used to remove residual noise of enhanced spectrum. In this paper, we propose a combined loss to further improve speech enhancement. In order to effectively remove the residual noise in the speech, the positive part of the Triplet loss is used with the component loss. For the experiment TIMIT database is re-constructed using NOISEX92 noise and background music samples with various Signal to Noise Ratio (SNR) conditions. Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligibility (STOI) are used as the metrics of performance evaluation. When the VF was trained with the mean squared error and the SI model was trained with the combined loss, SDR, PESQ, and STOI were improved by 0.5, 0.06, and 0.002 respectively compared to the system trained only with the mean squared error.

• Journal of Korean Theatre Studies Association
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• no.48
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• pp.421-446
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• 2012

The purpose of this paper is to shed light onto the historical significance and limitations of the Tsukiji Little Theater's modern performances. The Tsukiji Little Theater holds a position of great importance to the history of both Japanese and Korean modern theater. Some, however, are under the completely opposite impression. There are also mixed opinions about whether the Tsukiji Little Theater is a "model example" of the modern theatrical movement or a "bad example". Based on this controversy, we look into the definitive characteristics of the Tsukiji Little Theater based mostly on "the controversy over translated foreign plays", "the controversy of foreign plays versus original plays", "the value of kabuki" and "Shinpa as a rival". This paper looked into the differences in controversy over translated foreign plays in the Tsukiji Little Theater and the controversy in existing translated foreign plays. It mostly looks at the "casuistry of foreign plays" and the "cultural engineering theory of foreign plays"to get a grasp on the controversy surrounding existing translated foreign plays. Meanwhile, the "internally critical meaning" towards the original plays of renowned writers was strong in the controversy of foreign plays in the Tsukiji Little Theater. Kaoru Osanai defined the 1920s as a dark period, and persisted that because of the activity of the Shingeki movement, foreign plays were needed instead of low-level original plays. This study examines the characteristics of original plays and foreign plays publicly performed at the Tsukiji Little Theater to analyze the "controversy of translated foreign plays versus original plays". The Tsukiji Little Theater mostly put on shows with a strong sense of resistance or that defied the old times. This caused there to be a lot of emphasis put on the rebellious mindset towards old conventions and ideologies for most of the plays, both foreign and original, and the problem arises that little mind was paid to the integrity or beauty of the works. In looking at the "value of kabuki", this paper looked into Kaoru Osanai, who was deeply involved in kabuki actors. He evaluated traditional Japanese arts highly not because of the literary value of their scripts, but because he recognized the value of how they were performed. In order to create a new spectacle, music, dance and mime was taken in from countries around the world, and kabuki was regarded highly as a means of expression on stage. Finally, we also examine the recognized reasons for treating Shinpa as a rival. There is a relationship between these reasons and a complex about the audiences they drew. The Shinpa performances always had many spectators and were successful, but those at the Tsukiji Little Theater were so unpopular with the public that it was hard for them to financially run their theater group. The empty seats in their theater constantly made the modern intellectuals in the Shingeki movement feel inferior.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.409-418
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• 2022

In this paper, we propose SAAnnot-C3Pap, a semi-automatic annotation method for obtaining ground truth of a player's posture. In order to obtain ground truth about the two-dimensional joint position in the existing music domain, openpose, a two-dimensional posture estimation method, was used or manually labeled. However, automatic annotation methods such as the existing openpose have the disadvantages of showing inaccurate results even though they are fast. Therefore, this paper proposes SAAnnot-C3Pap, a semi-automated annotation method that is a compromise between the two. The proposed approach consists of three main steps: extracting postures using openpose, correcting the parts with errors among the extracted parts using supervisely, and then analyzing the results of openpose and supervisely. Perform the synchronization process. Through the proposed method, it was possible to correct the incorrect 2D joint position detection result that occurred in the openpose, solve the problem of detecting two or more people, and obtain the ground truth in the playing posture. In the experiment, we compare and analyze the results of the semi-automated annotation method openpose and the SAAnnot-C3Pap proposed in this paper. As a result of comparison, the proposed method showed improvement of posture information incorrectly collected through openpose.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.447-454
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• 2022

In the era of the 4th industrial revolution, we are living in a flood of information. It is very difficult and complicated to find the information people need in such an environment. Therefore, in the flood of information, a recommendation system is essential. Among these recommendation systems, many studies have been conducted on each recommendation system for movies, music, food, and clothes. To date, most personalized recommendation systems have recommended clothes, books, or movies by checking individual tendencies such as age, genre, region, and gender. Future generations will want to be recommended clothes, books, and movies at once by checking age, genre, region, and gender. In this paper, we propose a recommendation system that recommends personalized clothes and food at once according to the user's emotions and weather. We obtained user data from Twitter of social media and analyzed this data as user's basic emotion according to Paul Eckman's theory. The basic emotions obtained in this way were converted into colors by applying Hayashi's Quantification Method III, and these colors were expressed as recommended clothes colors. Also, the type of clothing is recommended using the weather information of the visualcrossing.com API. In addition, various foods are recommended according to the contents of comfort food according to emotions.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.67-72
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• 2019

Animation is a comprehensive audio-visual art, animation literature, painting, music, architecture, photography and other art forms are integrated. China's animation industry has made some achievements in the new century, but on the whole, with the globalization of China, China's animation industry has been influenced by Japan and the United States. China has a history and culture of five thousand years, with profound social deposits and cultural foundation. Of the four ancient civilizations in the world, the Chinese civilization is the only one that has survived. China has too many stories to tell. From the development history of Chinese and foreign animation, we can see that many Chinese traditional cultural elements are used for reference. Since the 1980s, Chinese animation has been on the road of national revival. Chinese animation has begun to draw close to traditional culture in terms of themes, characters and scenes, and integrate Chinese traditional cultural elements. The theme of big fish and begonia is to repay kindness by sacrificing one's own life for the sake of justice and friendship. This fearless spirit of sacrificing one's life for justice is the concentrated embodiment of the fine qualities of the Chinese nation over the past several thousand years. Kun to save chun and give up his life, chun in order to repay rather give up half of his life, and qiushui in order to help their beloved, also would rather give up all of their own. These three protagonists are very distinctive personality characteristics, are to "righteousness" and give up their most precious things. At the same time, big fish and begonia combines many traditional Chinese cultural elements to form an animated film with Chinese characteristics.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.253-266
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• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.3
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• pp.42-50
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• 2012

City squares are public open spaces which are closely related to the peoples daily lives. Most squares are located in the center of the city, and they are usually used for community gatherings and they are suitable for open markets, music concerts, political rallies, and other events. City squares also play an important role as a grand public place operating in multi functions that require involvement of more people. The purpose of this study is to examine satisfaction on the spatial components, characteristics, and the user satisfaction in City Squares. The slady also analyzed the relationship between the satisfaction about spatial components, characteristics and it also shows that the user satisfaction is followed. This study sites are made in 3 grand public places in the center of Seoul including the Seoul plaza, Cheonggye Plaza, and Gwanghwarnun Square. Data were analyzed using several statistical methods such as descriptive statistics, factor analysis, ANOVA, correlation and regression. Results of the study are as follows: First, factor analysis carried out to extract the various factors of satisfaction on the sites; spatial components, usability, amenity/security, and spatial characteristics. User satisfaction concerning usability factor was higher than the satisfaction of the other factors. This result represented that the slady sites play an important role to the public open spaces in the city. Second, users showed high user satisfaction to study sites, and user satisfaction rate toward the Gwanghwarnun Square is the highest because of its facility planuing. Finally, user satisfactim was strongly correlated on the usability factor of spatial planning. Also, the significant correlations between the user satisfaction and the other factors such as spatial components, security, and spatial characteristics of spatial planning are presented. Results of this study can help guide the planning and management of the city square as a public open space based on the understanding of user perception and satisfaction.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.161-171
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• 2019

The purposes of this study are: 1) to verify the systems thinking factor structure of elementary school students and 2) to compare systems thinking according to their preferred subjects in order to get implications for following research. For the study, pre-tests analyze data from 732 elementary school students using the STMI (Systems Thinking Measuring Instrument) developed by Lee et al. (2013). And exploratory factor analysis was conducted to identify the factor structure of the students. Based on the results of the pre-test, the expert group council revised the STMI so that elementary school students could respond to the 5-factor structure that STMI intended. In the post-test, 503 data were analyzed by modified STMI and exploratory factor analysis was performed. The results of the study are as follows: First, in the pre-test, elementary school students responded to the STMI with a test paper consisting of two factors (personal internal factors and personal external factors). The total reliability of the instrument was .932 and the reliability of each factor was analyzed as .857 and .894. Second, for modified STMI, elementary school students responded a 4-factor instrument. Team learning, Shared Vision, and Personal Mastery were derived independent factors, and mental model and systems analysis were derived 1-factor. The total reliability of the instrument was .886 and the reliability of each factor was analyzed as .686 to .864. Finally, a comparison of systems thinking according to preferred subjects showed a significant difference between students who selected science (engineering) group and art (music and physical education). In conclusion, it was confirmed that statistically meaningful results could be obtained using STMI modified by term and sentence structure appropriate for elementary school students, and it is a necessary to study the relation of systems thinking with various student variables such as the preferred subjects.