• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1412-1417
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• 2004

Sparse coding or independent component analysis (ICA) which is a holistic representation, was successfully applied to elucidate early auditor${\gamma}$ processing and to the task of sound classification. In contrast, parts-based representation is an alternative way o) understanding object recognition in brain. In this thesis we employ the non-negative matrix factorization (NMF) which learns parts-based representation in the task of sound classification. Methods of feature extraction from the spectro-temporal sounds using the NMF in the absence or presence of noise, are explained. Experimental results show that NMF-based features improve the performance of sound classification over ICA-based features.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.231-238
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• 2006

In this paper, the method to make lossless image compression that holds considerable part of total volume of mobile game has been proposed. To increase the compression rate, we compress the image by Deflate algorithm defined in RFC 1951 after reorganize it at preprocessing stage before conducting actual compression. At the stage of preprocessing, we obtained the size of a dictionary based on the information of image which is the feature of Dictionary-Based Coding, and increased the better compression rate than compressing in a general manner using in a way of restructuring image by pixel packing method and DPCM prediction technique. It has shown that the method increased 9.7% of compression rate compare with existing mobile image format, after conducting the test of compression rate applying the suggested compression method into various mobile games.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.1-12
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• 2016

Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.516-521
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• 2010

In the high-speed packet service, next generation mobile communication system has emerged as a major feature. If the fire of these high-speed D kit services and non-continuous transmission of data due to the symmetrical nature of daeyiteo traffic for D-CDMA system has been actively studied. In this paper, we apply turbo codes for D-CDMA has been investigated. Considering the nature of the system configuration of the transmission frame type, such as physical channel structure and channel coding has been investigated. In addition to TD-CDMA system, one HARQ gibeopjung hase Combining the performance analysis techniques were applied.

• Journal of Broadcast Engineering
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• v.6 no.3
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• pp.215-224
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• 2001

In recent days, research activities on multimedia services mainly focus on the multiplexing system with timing synchromization for media components, such as video, audio and text. The MPEG-4 standard emphasizes object-based coding which includes analysis and understanding of the Image content. Since in MPEG-4 we can define objects and encode them independently, we can manipulate and display each object for different applications. This feature of MPEG-4 is also vero useful for multimedia services, such as video streaming cia different network channels, digital versatile disc, internet TV, video E-mail, and so on. In this Paper, we implement a multimedia streaming system which is compliant with the MPEG-4 system and the MP4 file format.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.425-435
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• 2002

This paper introduces a macroblock-based rate control algorithm using the neural classifier based in Self Organization feature Maps (SOFM). In contrast to the conventional rate control methods based on the mathematical rate distortion (RD) model and the feedback regression, proposed method can actively adapt to the rapid-varying image characteristics by establishing the global model for bitrate control and by using the SOFM based neural classifier to manage that model. Proposed rate control algorithm has 0.2 dB ~ 0.6 dB better performances than MPEG-4 macroblock-based rate control algorithm by evaluating with the encoded Peak Signal to Noise Ratios while maintaining similar overall computational complexity.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.97-102
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• 2007

In this paper, a new architecture for fast-serial $GF(2^m)$ multiplier with low hardware complexity is proposed. The fast-serial multiplier operates standard basis of $GF(2^m)$ and is faster than bit serial ones but with lower area complexity than bit parallel ones. The most significant feature of the fast-serial architecture is that a trade-off between hardware complexity and delay time can be achieved. But The traditional fast-serial architecture needs extra (t-1)m registers for achieving the t times speed. In this paper a new fast-serial multiplier without increasing the number of registers is presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• Fourth Industrial Review
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• v.2 no.1
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• pp.9-17
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• 2022

Purpose -In general, elementary school is the time to take the first social step away from family relationships with parents or siblings. Recently, AI technology has been widely used in everyday life and society. The purpose of this study is to propose a program that can cultivate AI literacy and self-expression for elementary school students according to the trend of the times. Research design, data, and methodology - In this study, prior to developing a self-expression class program for cultivating AI literacy, we looked at the related literature on what AI literacy is. In addition, the digital learning program was analyzed considering that the current AI literacy is based on the cutting edge of digital technology and is located in the same area as digital literacy. Result -This study developed a curriculum for self-expression and AI literacy cultivation. The main feature of this study is that the education program of this study allows 3rd, 4th, and 5th graders of elementary school to express themselves and to express their career problems by combining culture and art with AI programs. Conclusion -Self-expression activity education for cultivating AI literacy should be oriented toward holistic education and should be education as a way to express oneself in order to improve the quality of life of learners