• Cartoon and Animation Studies
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• s.9
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• pp.266-282
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• 2005

Cartoon & Animated cartoon is consists of imaginal attributes and linguistic attributes, and it is closely connected with humor and satirical contents. And then various expressions using animals as matter communicate satirical attributes of a satire strongly and easily. On this article, techniques of satirical expression using animals in Cartoon & Animated cartoon media are studied and analyzed. By the method, it looks around briefly beginning from primitive cave paintings of the prehistoric age to various contemporary Cartoon & Animated cartoon character industries as historical background of Cartoon & Animated cartoon, and also arranges various types that literary expression and representation for visual expression techniques - metaphorical expressions, emblematic expressions, figure of speech and so forth - on literature. This attempt aims for presenting a basic analysis method that connecting and combining Cartoon & Animated cartoon media with humanistic classification and making database of existing data. These accumulated data will indicate cartoon and the action of meaning.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.573-585
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• 2018

Services for navigation and entertainment through AI-based voice user interface devices are becoming popular in the connected car system. Given the classification of VUI agent developers as IT companies and automakers, this study explores attributes of agent persona and user experience that impact the driver's perceived safety and satisfaction. Participants of a car simulator experiment performed entertainment and navigation tasks, and evaluated the perceived safety and satisfaction. Results of regression analysis showed that credibility of the agent developer, warmth and attractiveness of agent persona, and efficiency and care of the UX dimension showed significant impact on the perceived safety. The determinants of perceived satisfaction were unity of auto-agent makers and gender as predisposing factors, distance in the agent persona, and convenience, efficiency, ease of use, and care in the UX dimension. The contributions of this study lie in the discovery of the factors required for developing conversational VUI into the autonomous driving environment.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.299-303
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• 2017

By piling up hidden layers in artificial neural networks, deep learning is delivering outstanding performances for high-level abstraction problems such as object/speech recognition and natural language processing. Alternatively, deep-learning users often struggle with the tremendous amounts of time and resources that are required to train deep neural networks. To alleviate this computational challenge, many approaches have been proposed in a diversity of areas. In this work, two of the existing Apache Spark-based acceleration frameworks for deep learning (SparkNet and DeepSpark) are compared and analyzed in terms of the training accuracy and the time demands. In the authors' experiments with the CIFAR-10 and CIFAR-100 benchmark datasets, SparkNet showed a more stable convergence behavior than DeepSpark; but in terms of the training accuracy, DeepSpark delivered a higher classification accuracy of approximately 15%. For some of the cases, DeepSpark also outperformed the sequential implementation running on a single machine in terms of both the accuracy and the running time.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.37-46
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• 2001

This paper proposes a new noise suppression method using the Wavelet transform analysis. The noise suppressor using the Wavelet transform shows the more effective advantages in a babble noise than one using the short-time Fourier transform. We designed a new channel structure based on spectral subtraction of Wavelet transform coefficients and used the Wavelet mask pattern with more higher time resolution in high frequency. It showed a good adaptation capability for babble noise with a non-stationary property. To evaluate the performance of proposed noise canceller, the informal subjective listening tests (Mos tests) were performed in background noise environments (car noise, street noise, babble noise) of mobile communication. The proposed noise suppression algorithm showed about MOS 0.2 performance improvements than the suppression algorithm of EVRC in informal listening tests. The noise reduction by the proposed method was shown in spectrogram of speech signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3036-3044
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• 2010

With the rapid growth of video data service, demand to provide advertisements or additional information with regard to a particular video scene is increasing. However, the direct use of automated visual analysis or speech recognition on videos virtually has limitations with current level of technology; the metadata of video such as title, category information, or summary does not reflect the content of continuously changing scenes. This work presents a new video contextual advertising system that serves relevant advertisements on a given scene by leveraging the scene's situation information inferred from video scripts. Experimental results show that the use of situation information extracted from scripts leads to better performance and display of more relevant advertisements to the user.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.50-55
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• 2016

To attain an understanding of customers' opinions or demands regarding a companies' products or service, it is important to consider VOC (Voice of Customer) data; however, it is difficult to understand contexts from VOC because segmented and duplicate sentences and a variety of dialog contexts. In this article, POS (part of speech) and morphemes were selected as language resources due to their semantic importance regarding documents, and based on these, we defined an LSP (Lexico-Semantic-Pattern) to understand the structure and semantics of the sentences and extracted summary by key sentences; furthermore the LSP was introduced to connect the segmented sentences and remove any contextual repetition. We also defined the LSP by categories and classified the documents based on those categories that comprise the main sentences matched by LSP. In the experiment, we classified the VOC-data documents for the creation of a summarization before comparing the result with the previous methodologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.758-761
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• 2007

Digital signal processing technique is applied in wide fields such as speech processing, image processing and spectrum analysis. Therefore, in order to do frequency selective operation digital filter is used in stead of analog filter and sharp filter characteristics can be implemented. Since finite impulse response (FIR) digital filter as nonrecursive type represents linear phase response characteristics and is always stable and is used in fields regarding wave information importantly such as data transmission. And due to frequency characteristics, in order to remove the Gibbs phenomenon generating around a discontinuous point, filter is designed through window function method. Therefore, in this paper to improve performance of FIR digital filter, a modified window function was applied. And the proposed method was compared with conventional methods using peak side-lobe and transition properties in simulations.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.209-214
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• 2017

The aim of the present study was to analyze the factors that affects the peer attachment in Korean youth. Subjects were 419 middle school students (210 male, 209 female). Dependent variable was defined as peer attachment. Explanatory variables were included as gender, academic achievement satisfaction, subjective household economy level, parent - child dialogue frequency, subjective health status, depression symptom, self - esteem, subjective life satisfaction, and mobile phone dependency. In the multi-layer perceptron artificial neural network algorithm analysis, depression symptoms, gender, parent-child dialogue level for school life, subjective household economy level, subjective health status were significantly associated with peer attachment in Korean youth. Based on this result, systematic programs are required in order to prevention of peer attachment in Korean youth.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.293-298
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• 2017

The purpose of this study was to analyze the risk factors of depression in elementary school students in Korea. The subjects of the study were 23,291 elementary school students (12,016 male, 11,275 female) aged 9 to 12 years. Dependent variable was defined as experience of depression. Explanatory variables were included as sex, residential areas, social discrimination experience, experience of school violence for the past year, experience of Korean language education, experience of using multicultural family support center, reading to Korean, speaking to Korean, and writing to Korean, listening to Korean. In the RBF neural network analysis, experience of Korean education, experience of school violence, experience of Korean social discrimination, level of Korean reading were significantly associated with depression in elementary school students. In order to prevent depression in multicultural children, priority attention and counseling are needed for the group whose level of Korean reading is low.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.3
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• pp.172-178
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• 1986

The recent interest in the design of filters is motivatied by the fact that such filter can be fully integrated using standard metal-oxide-semiconductor processing technology. This is due to replacing all the resistors in the active RC filter network by the switched capacitors. The voltage gain of a SC filter depends only on the rations of capacitance and these ratios can be obtained and maintained to high accuracy. Therefore, it is known that a switched capacitor is much better than a resistor in temperature and linearity characteristics. This paper proposed a programmable SC filter and proved the fact that ${omega}_0$ Q and G of this circuit can be controlled by digital signal. Experiments show that SC filter remains the low sensitivities but it can't avoid little influence of parasitic capacitance. As the transfer characteristic of the SC filter is varied with sampling frequency and resistor array, SC filtering technigue can be applied for digital processing, speech analysis and synthesis and so on.