• Journal of Industrial Technology
• /
• v.17
• /
• pp.331-338
• /
• 1997

In this paper, we propose a new neural pattern recognition from wavelet transform. We first analysis in BFT(Binary Field Transform) in character image. The proposed neural network and wavelet transform is able to improve learning time and scaling. The ability and effectiveness of identifying image using the proposed wavelet transform will be demonstrated by computer simulation.

• Journal of Korea Game Society
• /
• v.21 no.4
• /
• pp.117-130
• /
• 2021

The purpose of this paper is to study users' intention on paid game items through language network analysis. The functional item buying group considered the capabilities and strength of the game character as the most important factor for the winning of the games while the decorative game item buying users considered self-satisfaction for the unique outfit of their game character. Moreover, they reflected their game characters as themselves and another ego.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.11
• /
• pp.3984-3996
• /
• 2014

Mobile social network can be seen as a specific application of the DTN (Delay Tolerant Network), in which the information propagation can be impacted by many social behaviors of the nodes. For a specific node, its social behaviors are various. For example, the node may not be interested in the information before receiving it and may also discard the information after getting it. On the other hand, people are more willing to forward the message to his friends. These interactive behaviors between nodes can be seen as social behaviors. It is easy to see that the impact of the social behaviors is related to the social ties, which can be manifested by the structure of the social network. State of the art works often simply assumes that the social networks can be divided into some communities. At present, some works find that the structure of some social networks is scale-free. To overcome this problem, this paper proposes a theoretical model to evaluate the impact of above social behaviors in the DTN-like scale-free network. Simulation shows the accuracy of the model. Numerical results show that both social behaviors and scale-free character have significant impact on information propagation. Moreover, the impact of social behaviors is related to the scale-free character of the networks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.90-95
• /
• 2002

This thesis is aiming at analysis and implementing Distance Video Lecturing System to guarantee the high quality in service through using less Network resource. Most of the usual Distance Video Lecturing System has been designed not in the system of Multiuser Conference but Point-to-Point. But from now on Distance Video Lecturing System is to be demanded on not only the expansion to Multiuser Distance Video Lecturing System, but high quality in service for users. To solve these problems, the Multicast Transmission Technology as the dimension of Network as well as highly efficient, advanced Compression Technology should be applied to Video Conference System in company with the expansion of Network bandwidth. The system suggested in this thesis is to help to offer an application service as Distance Video Lecturing System that will make popular on the basis of the character that the next generation Internet will be high speed Network.

• Trans-
• /
• v.13
• /
• pp.141-169
• /
• 2022

Analysis of narrative texts has been regarded as academically and practically important, and has been made from various perspectives and methods. In this paper, the computational narrative analysis methodology from the perspective of information processing was examined. From the point of view of information processing, the creation and acceptance of narrative is a bidirectional coding process mediated by narrative text, and narrative text can be said to be a multi-layered structured code. In this paper, four methodologies that share this point of view - character network analysis, text mining and sentiment analysis, continuity analysis of event composition, and knowledge analysis of narrative agents - were examined together with cases. Through this, the mechanism and possibility of computational methodology in narrative analysis were confirmed. In conclusion, the significance and side effects of computational narrative analysis were examined, and the necessity of designing a human-computer collaboration model based on the consilience of the humanities and science/technology was discussed. Based on this model, it was argued that aesthetically creative, ethically good, politically progressive, and cognitively sophisticated narratives could be made more effectively.

• Communications for Statistical Applications and Methods
• /
• v.6 no.3
• /
• pp.831-842
• /
• 1999

We propose a wavelet decomposition feature extraction method for the hand-written character recognition. Comparing the recognition rates of which methods with original image features and with selected features by the wavelet decomposition we study the characteristics of the proposed method. LDA(Linear Discriminant Analysis) QDA(Quadratic Discriminant Analysis) RDA(Regularized Discriminant Analysis) and NN(Neural network) are used for the calculation of recognition rates. 6000 hand-written numerals from CENPARMI at Concordia University are used for the experiment. We found that the set of significantly selected wavelet decomposed features generates higher recognition rate than the original image features.

• Journal of Digital Convergence
• /
• v.9 no.6
• /
• pp.231-242
• /
• 2011

The purpose of this study are as follows. First, to analyze relative LQ index of the No. of character company, the No. of employee and the amount of revenue. Second, to analyze the strength and weakness about technology competence, human resource competence, infra competence and network competence of regional character contents R&D. The results are as follows. The relative competitively LQ index results of company infra indicated all regional area are over 1 LQ index. But, in case of except of seoul & kyunggi, the competence LQ index of R&D which is jeju, dongnam(pusan & kyungnam) are in order. Final result suggested that the high competitiveness of regional character industry are seoul & kyunggi, jeju, dongnam area.

• Journal of Information Display
• /
• v.5 no.3
• /
• pp.35-40
• /
• 2004

In this study, we collected data used to formulate the relationship between quantitative metrological parameters in CRT display and the perceived focus quality. Human perception of the focusing quality was evaluated in terms of user feedback scores regarding the character legibility from four highly trained inspectors. Thirteen CRT monitors from five different manufacturers were compared relatively with respect to the norm monitor. The profile of electron beam such as spot size and the shape of distribution made by electron beam, contrast, convergence of RGB beams, and luminance characteristics were measured using a precision measurement system. Linear regression analysis and artificial neural network models were used to formulate the relationship between human perception and the quantitative measurements. The accuracy of the formulated linear regression model ($R^2$=0.515) was not satisfactory but the nonlinear neural network model ($R^2$=0.716) was fairly convincing and robust even the utilized data included subjective differences.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.265-271
• /
• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• Journal of Korea Multimedia Society
• /
• v.22 no.4
• /
• pp.455-462
• /
• 2019

This paper proposes a method of utilizing convolutional neural network to classify the images of Bender Gestalt Test (BGT), which is a tool to understand and analyze a person's characteristic. The proposed network is composed of 29 layers including 18 convolutional layers and 2 fully connected layers, where the network is to be trained with augmented images. To verify the proposed method, 10 fold validation was adopted. In results, the proposed method classified the images into 9 classes with the mean f1 score of 97.05%, which is 13.71%p higher than a previous method. The analysis of the results shows the classification accuracy of the proposed method is stable over all the patterns as the worst f1 score among all the patterns was 92.11%.