• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.715-720
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• 2020

In Big data analysis, text data is mostly unstructured and large-capacity, so analysis was difficult because analysis techniques were not established. Therefore, this study was conducted for the possibility of commercialization through verification of usefulness and problems when applying the big data word cloud technique, one of the text data analysis techniques. In this paper, the limitations and problems of this technique are derived through visualization analysis of the "President UN Speech" using the R program word cloud technique. In addition, by proposing an improved model to solve this problem, an efficient method for practical application of the word cloud technique is proposed.

• Journal of Engineering Education Research
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• v.10 no.3
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• pp.109-124
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• 2007

With the advance of the Internet and computing technologies, e-learning is now a hot issue worldwide for providing the effective learning on the cyber-space. However, most of existing e-learning contents have been developed mainly based on text, including simple multimedia elements such as images, animations, and voices. This paper suggests a method effective for the computer programming e-learning. The method is based on program visualization using flowcharts. It features the stepwise hierarchical program visualization on the level of statements, the flowchart based visualization for control constructs of languages, visualization over whole programs, visualization compared with source codes, and interaction with users. Finally, we implement a system to realize the suggested method, and execute it for an example program.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.533-542
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• 2011

Visualization elements as the technology to offer information to users effectively have become more important. In this study, we evaluate the usefulness of visualization elements in InSciTe which is a technology intelligence service developed by using Semantic Web technologies and text mining technologies for establishing R&D strategy using papers and patents. We propose design which can be preferred by users and applying methods of visualization elements through the quantitative and qualitative evaluation about each types of service. As a result of evaluation, we conclude that the visualization elements in InSciTe are implemented user-friendly to improve user's cognitive intuition.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2434-2444
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• 1997

As software industry progresses, the necessity of visual information have increased more than text-oriented information. So, automatic tools are required to satisfy a user's desire for visual design representation of various source information in the real-world. In this paper, we discuss the methodology and tools for parsing abstract information through semantic analysis and extracting visual information through visual mapping. Namely, as to abstract informations are represented as relational structure and then mapped into visual structure using regular rule, user can obtain visual information. We suggest VOLS(Visual Object Layout System) to transform a abstract information to visual information. It can improve user understandability and assist a maintenance for existing source code.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.999-1007
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• 2013

This research shows several types of moving pictures from the data: 1) the word cloud of Korean texts, 2) the heat map of n ${\times}$ p matrices, 3) the moving image of p ${\times}$ p scatterplot matrix, 4) the local projective display of k clusters (Huh and Lee, 2012). Moving pictures may reveal the hidden information and beauty of the datasets and ignite the curiosity of information consumers. Video files are attached.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.178-184
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• 2023

Finding texts in general scene images and recognizing their contents is a very important task that can be used as a basis for robot vision, visual assistance, and so on. However, for the low-resolution text images, the degradations, such as noise or blur included in text images, are more noticeable, which leads to severe performance degradation of text recognition accuracy. In this paper, we propose a new Korean text image super-resolution based on a Transformer-based model, which generally shows higher performance than convolutional neural networks. In the experiments, we show that text recognition accuracy for Korean text images can be improved when our proposed text image super-resolution method is used. We also propose a new Korean text image dataset for training our model, which contains massive HR-LR Korean text image pairs.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.297-302
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• 2022

Contemporary viewers familiar with the digital space show their desire for self-expression and use voice, text and gestures as tools for expression. The purpose of this study is to create interactive art that expresses the narrative uttered by the viewer in the form of a collage using the viewer's figure, and reproduces and expands the story by the viewer's movement. The proposed interactive art visualizes audio and video information acquired from the viewer in a text collage, and uses gesture information and a natural user interface to easily and conveniently interact in real time and express personalized emotions. The three pieces of information obtained from the viewer are connected to each other to express the viewer's current temporary emotions. The rigid narrative of the text has some degree of freedom through the viewer's portrait images and gestures, and at the same time produces and expands the structure of the story close to reality. The artwork space created in this way is an experience space where the viewer's narrative is reflected, updated, and created in real time, and it is a reflection of oneself. It also induces active appreciation through the active intervention and action of the viewer.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.16-23
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• 2013

This paper analyzes the artistic practical use of social network visualization through the aesthetic information interpretation. The first social network visualization has emerged as 'Sociogram' in the form of social network analysis(SNA). Since social network has complex, the analyzing technology of social network has emerged. Early social network visualization has a practical purpose to measure the social structure, but current social network visualization divided into various forms from artistic expressions through information. This paper divide into two categories based on the artistic application of social network visualization. First, this research focuses on the static graph based on analog. Second, this research analyze the category of interacted visualization to generate a real-time digital image. This paper presents the fusion of paradigm between engineering and art through this way.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.63-70
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• 2015

Program source code is a set of complex syntactic information which are expressed in text forms, and contains complex logical structures. Structural and logical complexity inside source code become barriers in applying visualization techniques shown in traditional big-data approaches when the volume of source code become over ten-thousand lines of code. This paper suggests a procedure for making visualization of structural characteristics in source code. For this purpose, this paper defines internal data structures as well as inter-procedural relationships among functions. The paper also suggests a means of outlining the structural characteristics of source code by visualizing the source codes with network forms The result of the research work can be used as a means of controling and understanding the massive volume of source code.