• Journal of Science of Art and Design
• /
• v.8
• /
• pp.267-296
• /
• 2005

Typography, as the median for communication, has expanded its roles according the attributes of the media where it Is used, and the change of media follwing the change of times is presenting new directions to the field of typography. The attempts of 20C experimental typography prioritize visual formativeness, free typography and language started to appear on printed matters and different kinds of prints put pep in magazines. Thus, experiments in the aspects of effective delivery of inpormation that letters have and aesthetic side of shapes of letter are continuing. Today with the appearance of multimedia, development of visual colture and rapid development of digital technology, the range of experimental typography has expanded even wider and therefore, different kinds of expressions became possible. As seen above, unlike the existing static printed media that carries linguistic information only, letters in the multimedia environment is shown in the movie titles, TV or web not only as a basic visual media such as type and image, but as a dynamic and complex factor that contains additional information of motion and sound factor. This study will attempt to find the historic context of focus of moment from the kinetic art and define the moving letters as kinetic typography. Therefore, this paper will have an understanding on kinetic typography's background, concept and characteristics following the change of communication environment in the multimedia era and tried to study the basic theories of kinetic typography and the information delivery and imagery function of letters. Also, this paper attempted to carry out a study on whether kinetic typography is delivering information smoothly from the aspect of communication through the image role as delivering information by studying major works of artists who have influenced kinetic typography. Based on this study, I would like to suggest new direction for effective delivery of information and value of use.

• (The) Research of the performance art and culture
• /
• no.43
• /
• pp.5-46
• /
• 2021

The film Moranbong is the product of a trip to North Korea in 1958, when Armangati, Chris Marker, Claude Lantzmann, Francis Lemarck and Jean-Claude Bonardo left at the invitation of Joseon Film. However, for political reasons, the film was not immediately released, and it was not until 2010 that it was rediscovered and received attention. The movie consists of the narratives of Young-ran and Dong-il, set in the Korean War, that are folded into the narratives of Chunhyang and Mongryong in the classic Chunhyangjeon of Joseon. At this time, Joseon's classics are reproduced in the form of the drama Chunhyangjeon, which shares the time zone with the two main characters, and the two narratives are covered in a total of six scenes. There are two layers of middle-story frames in the movie, and if the same narrative is set in North Korea in the 1950s, there is an epic produced by the producers and actors of the Changgeuk Chunhyangjeon and the Changgeuk Chunhyangjeon as a complete work. In the outermost frame of the movie, Dong-il is the main character, but in the inner double frame, Young-ran, who is an actor growing up with the Changgeuk Chunhyangjeon and a character in the Changgeuk Chunhyangjeon, is the center. The following three OST albums are Corée Moranbong released in France in 1960, Musique de corée released in 1970, and 朝鮮の伝統音樂-唱劇 「春香伝」と伝統樂器- released in 1968 in Japan. While Corée Moranbong consists only of the music from the film Moranbong, the two subsequent albums included additional songs collected and recorded by Pyongyang National Broadcasting System. However, there is no information about the movie Moranbong on the album released in Japan. Under the circumstances, it is highly likely that the author of the record label or music commentary has not confirmed the existence of the movie Moranbong, and may have intentionally excluded related contents due to the background of the film's ban on its release. The results of analyzing the detailed scenes of the Changgeuk Chunhyangjeon, Farewell Song, Sipjang-ga, Chundangsigwa, Bakseokti and Prison Song in the movie Moranbong or OST album in the 1950s are as follows. First, the process of establishing the North Korean Changgeuk Chunhyangjeon in the 1950s was confirmed. The play, compiled in 1955 through the Joseon Changgeuk Collection, was settled in the form of a Changgeuk that can be performed in the late 1950s by the Changgeuk Chunhyangjeon between 1956 and 1958. Since the 1960s, Chunhyangjeon has no longer been performed as a traditional pansori-style Changgeuk, so the film Moranbong and the album Corée moranbong are almost the last records to capture the Changgeuk Chunhyangjeon and its music. Second, we confirmed the responses of the actors to the controversy over Takseong in the North Korean creative world in the 1950s. Until 1959, there was a voice of criticism surrounding Takseong and a voice of advocacy that it was also a national characteristic. Shin Woo-sun, who almost eliminated Takseong with clear and high-pitched phrases, air man who changed according to the situation, who chose Takseong but did not actively remove Takseong, Lim So-hyang, who tried to maintain his own tone while accepting some of modern vocalization. Although Cho Sang-sun and Lim So-hyang were also guaranteed roles to continue their voices, the selection/exclusion patterns in the movie Moranbong were linked to the Takseong removal guidelines required by North Korean musicians in the name of Dang and People in the 1950s. Second, Changgeuk actors' response to the controversy over the turbidity of the North Korean Changgeuk community in the 1950s was confirmed. Until 1959, there were voices of criticism and support surrounding Taksung in North Korea. Shin Woo-sun, who showed consistent performance in removing turbidity with clear, high-pitched vocal sounds, Gong Gi-nam, who did not actively remove turbidity depending on the situation, Cho Sang-sun, who accepted some of the vocalization required by the party, while maintaining his original tone. On the other hand, Cho Sang-seon and Lim So-hyang were guaranteed roles to continue their sounds, but the selection/exclusion patterns of Moranbong was independently linked to the guidelines for removing turbidity that the Gugak musicians who crossed to North Korea had been asked for.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.36 no.11
• /
• pp.1091-1097
• /
• 2012

Nowadays, some movie theaters provide additional sensory information in 3D movies to enhance visually induced motion perception. However, no studies have investigated how motion perception increases. Thus, in this study, we examined the effect of visual coherent sensory information on visually induced motion perception and quantification of sensory information. A visual stimulus rotated sinusoidally and visual coherent sensory information were applied as vibrations to a subject's foot. We measured the sway of the subject's body by using a force plate and somatosensory bar rotation that represents the subject's perception of the horizon using an encoder. By using this data, we obtained the weight of the sensory information using a Kalman filter. As a result, it was found that subjects rotated the somatosensory bar more when visual coherent vibrations were applied. The weight of vision also increased when visual coherent vibrations were applied. Thus, we can conclude that visual coherent sensory information tends to enhance visually induced motion perception and weight of vision.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.10
• /
• pp.1822-1828
• /
• 2006

A key-frame should be efficiently selected to distinguish bad information from the videos. A previous technique selecting a key-frame mostly consists of the transformation scene-centered. In the case of harmful videos containing the quaility of continuous changes, the technique makes the total rate be reduced by an unnecessary key-frame. This thesis suggests the technique selecting a key-frame, an entry of the distinguishing system by using the quality of changes between the frames. In the experiment of this technique, it was proved that over 90% of the bad information was distinguished by the selected key frame, and also time efficiency was proved by showing 68% of decrement compared to the numbers I-frame. Therefore, This technique makes the system efficient to distinguish bad information, and efficiently can contribute to the distribution of the healthy movie information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.358-361
• /
• 2011

The image shown on movie is purposes information and communication. For smooth communication, It borrows the character was a mystery to we can free and various interpretations from the perspective of consumers. it's induce interest. Current images of Fantasy used in the magical world of myth and modern gives satisfaction to ours. And various characters have been developed. It is especially directed in the past is not a from. And it is emerged as a symbolic and abstract from. Aesthetics of beautiful things that has changed from the grotesque, dan to the development. Therefore, Legendary character of the past reflect the present era, and was dismantled in the original meaning. Therefore, it is the center of that change, Myths about the character of borrowers to recognize that communication through to be able to maximize the expected.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.12
• /
• pp.93-100
• /
• 2019

Similarity computation is very crucial to performance of memory-based collaborative filtering systems. These systems make use of user ratings to recommend products to customers in online commercial sites. For better recommendation, most similar users to the active user need to be selected for their references. There have been numerous similarity measures developed in literature, most of which suffer from data sparsity or cold start problems. This paper intends to extract preference information as much as possible from user ratings to compute more reliable similarity even in a sparse data condition, as compared to previous similarity measures. We propose a new similarity measure which relies not only on user ratings but also on movie genre information provided by the dataset. Performance experiments of the proposed measure and previous relevant measures are conducted to investigate their performance. As a result, it is found that the proposed measure yields better or comparable achievements in terms of major performance metrics.

• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.5
• /
• pp.521-529
• /
• 2003

In this paper we present an improved method by using demographic information for overcoming the similarity miss-calculation from the sparsity problem in collaborative filtering recommendation systems. The similarity between a pair of users is only determined by the ratings given to co-rated items, so items that have not been rated by both users are ignored. To solve this problem, we add virtual neighbor's rating using demographic information of neighbors for improving prediction accuracy. It is one kind of extentions of traditional collaborative filtering methods using the peason correlation coefficient. We used the Grouplens movie rating data in experiment and we have compared the proposed method with the collaborative filtering methods by the mean absolute error and receive operating characteristic values. The results show that the proposed method is more efficient than the collaborative filtering methods using the pearson correlation coefficient about 9% in MAE and 13% in sensitivity of ROC.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.43-50
• /
• 2024

This paper evaluates the Korean sentiment analysis performance of large language models like GPT-3.5 and GPT-4 using a zero-shot approach facilitated by the ChatGPT API, comparing them to pre-trained Korean models such as KoBERT. Through experiments utilizing various Korean sentiment analysis datasets in fields like movies, gaming, and shopping, the efficiency of these models is validated. The results reveal that the LMKor-ELECTRA model displayed the highest performance based on F1-score, while GPT-4 particularly achieved high accuracy and F1-scores in movie and shopping datasets. This indicates that large language models can perform effectively in Korean sentiment analysis without prior training on specific datasets, suggesting their potential in zero-shot learning. However, relatively lower performance in some datasets highlights the limitations of the zero-shot based methodology. This study explores the feasibility of using large language models for Korean sentiment analysis, providing significant implications for future research in this area.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.141-154
• /
• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.7
• /
• pp.4528-4535
• /
• 2014

In this paper, a distributed evacuation system based on the positioning information of subway passengers is proposed. Recently, the subway station is becoming complicated by combining with shopping malls, and movie theaters. Compared to the increasing complexity of subway stations, evacuation systems are less complex. Subway passengers in each cell were estimated to use the access point in the subway cells and statistics information. The evacuation route is provided through a direction indicator and push alarm of a smart phone based on estimated the number of passengers and exit information of the subway station. Based on this schemes, a quick and safe evacuation system of subway passengers was proposed. The number of connection passengers was estimated using AP with OpenWrt embedded OS installed. The average error rate of the number of passenger was confirmed to be 15%, 17% and 23% at the confidence parameter of $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$, respectively, through a simulation. The possibility of the system through a simple experiment was examined.