• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.517-525
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• 2009

We propose a quality guaranteed scalable video streaming service over the Internet using a new rate adaptation algorithm. Because video data requires much more bandwidth rather than other types of service, therefore, quality of video streaming service should be guaranteed while providing friendliness with other service flows over the Internet. To successfully provide this, we propose a framework for providing quality-guaranteed streaming service using two-channel transport layer and rate adaptation of scalable video stream. In this framework, baseline layer for scalable video is transmitted using TCP transport for minimum qualify service. Enhancement layers are delivered using TFRC transport with layer adaptation algorithm. The proposed framework jointly uses the status of playout buffer in the client and the encoding rate of layers in media contents. Therefore, the proposed algorithm can remarkably guarantee minimum quality of streaming service rather than conventional approaches regardless of network congestion and the encoding rate variation of media content.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1300-1306
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• 2018

The purpose of this study is to see possibility of Char2Vec as alternative of Word2Vec that most famous word embedding model in Sentence Similarity Measure Problem by Deep-Learning. In experiment, we used the Siamese Ma-LSTM recurrent neural network architecture for measure similarity two random sentences. Siamese Ma-LSTM model was implemented with tensorflow. We train each model with 200 epoch on gpu environment and it took about 20 hours. Then we compared Word2Vec based model training result with Char2Vec based model training result. as a result, model of based with Char2Vec that initialized random weight record 75.1% validation dataset accuracy and model of based with Word2Vec that pretrained with 3 million words and phrase record 71.6% validation dataset accuracy. so Char2Vec is suitable alternate of Word2Vec to optimize high system memory requirements problem.

• The Journal of Engineering Research
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• v.5 no.1
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• pp.89-107
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and landuse, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Whanam 2 Area, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Composite contamination map was achieved as a final result by comparing modified DRASTIC potential and the amount of generation load of several contaminant sources logically. The result could suggest the predictability of the area of contamination potential on the respects of hydrogeological aspect and water quality.

• Membrane Journal
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• v.30 no.2
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• pp.79-96
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• 2020

Secondary energy conversion systems have been briskly developed owing to environmental issue and problems of fossil fuel. They are basically operated based on electro-chemical systems. In addition, ion exchange membranes are one of the significant factors to determine performance in their systems. Therefore, the ion exchange membranes in suitable conditions must be developed to improve the performance for the electro-chemical systems. These ion exchange membranes can be classified into various types such as cation exchange membrane, anion exchange membrane and bipolar membrane. Their membranes have distinct characteristics according to the chemical, physical and morphological structure. In this review, the types of ion exchange membranes and their fabrication processes are described with main characteristics. Moreover, applications of ion exchange membranes in newly developed energy conversion systems such as reverse electrodialysis, redox flow battery and water electrolysis process are described including their roles and requirements.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.347-354
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• 2007

Since large portal service providers started web services for 3D city models around the world using spatial imagery, the competition has been getting intense to provide the models with the higher quality and accuracy. The building models are the most in number among the 3D city model objects, and it takes much time and money to create realistic model due to various shapes and visual appearances of building object. The aforementioned problem is the most significant limitation for the service and the update of the 3D city model of the large area. This study proposed a method of generating realistic 3D building models with quick and economical texture mapping using multiple spatial imagery such as aerial photos or satellite images after reconstructed geometric models of buildings from building layers in digital maps. Based on the experimental results, the suggested method has effectiveness for the generation of the 3D building models using various air-borne imagery and satellite imagery quickly and economically.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.167-170
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• 2004

The stochiometric mix of evaporating materials for the $CuGaT_2$ single crystal thin films was prepared from horizontal furnance. Using extrapolation method of X-ray diffraction patterns for the $CuGaTe_2$ polycrystal, it was found tetragonal structure whose lattice constant $a_0$ and $c_0$ were 6.025 ${\AA}$ and 11.931 ${\AA}$, respectively. To obtain the single crystal thin films, $CuGaTe_2$ mixed crystal was deposited on throughly etched semi-insulator GaAs(100) substrate by the Hot Wall Epitaxy (HWE) system. The source and substrate temperature were $670^{\circ}C$ and $410^{\circ}C$ respectively, and the thickness of the single crystal thin films is $2.1{\mu}m$. The crystalline structure of single crystal thin films was investigated by the photoluminescence and double crystal X-ray diffraction (DCXD). From the photocurrent spectrum by illumination of perpendicular light on the c - axis of the $CuGaTe_2$ single crystal thin film, we have found that the values of spin orbit coupling ${\Delta}s.o$ and the crystal field splitting ${\Delta}cr$ were $0.079\underline{1}eV$ and $0.246\underline{3}eV$ at 10 K, respectively. From the PL spectra at 10K, the peaks corresponding to free bound excitons and D-A pair and a broad emission band due to SA is identified. The binding energy of the free excitons are determined to be $0.047\underline{0}eV$ and the dissipation energy of the donor-bound exciton and acceptor-bound exciton to be $0.049\underline{0}eV$, $0.055\underline{8}eV$, respectively.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.29-32
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• 2000

Layered video coding schemes allow the video information to be transmitted in multiple video bitstreams to achieve scalability. they are attractive in theory for two reasons. First, they naturally allow for heterogeneity in networks and receivers in terms of client processing capability and network bandwidth. Second, they correspond to optimal utilization of available bandwidth when several video qualify levels are desired. In this paper we propose a scalable video codec architectures with motion estimation, which is suitable for real-time audio and video communication over packet networks. The coding algorithm is compatible with ITU-T recommendation H.263+ and includes various techniques to reduce complexity. Fast motion estimation is Performed at the H.263-compatible base layer and used at higher layers, and perceptual macroblock skipping is performed at all layers before motion estimation. Error propagation from packet loss is avoided by Periodically rebuilding a valid Predictor in Intra mode at each layer.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.633-642
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• 2019

Recently, the convolution neural network (CNN) model at a single image super-resolution (SISR) have been very successful. The residual learning method can improve training stability and network performance in CNN. In this paper, we propose a SISR using recursive residual network architecture by introducing dense skip connections for learning nonlinear mapping from low-resolution input image to high-resolution target image. The proposed SISR method adopts a method of the recursive residual learning to mitigate the difficulty of the deep network training and remove unnecessary modules for easier to optimize in CNN layers because of the concise and compact recursive network via dense skip connection method. The proposed method not only alleviates the vanishing-gradient problem of a very deep network, but also get the outstanding performance with low complexity of neural network, which allows the neural network to perform training, thereby exhibiting improved performance of SISR method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.483-497
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• 2018

Image mosaicking, which combines several images into one image, is effective for analyzing images and important in various fields of spatial information such as a continuous image map. The crucial processes of the image mosaicking are optimal seamline determination and color correction of mosaicked images. In this study, the overlap regions were determined by SURF (Speeded Up Robust Features) for image matching. Based on the characteristics of the edges extracted by Canny filter, seamline candidates were selected from classified edges with their characteristics, and the edges were connected by using Dijkstra algorithm. In particular, anisotropic filter and image pyramid were applied to extract reliable seamlines. In addition, it was possible to determine seamlines effectively and efficiently by utilizing building and road layers from digital maps. Finally, histogram matching and seamline feathering were performed to improve visual quality of the mosaicked images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.27-32
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• 2019

Research that implements the classification process through Deep Learning algorithm, one of the outstanding human abilities, includes a unimodal model, a multi-modal model, and a multi-modal method using music videos. In this study, the results were better by suggesting a system to analyze each song's spectrum into short samples and vote for the results. Among Deep Learning algorithms, CNN showed superior performance in the category of music genre compared to RNN, and improved performance when CNN and RNN were applied together. The system of voting for each CNN result by Deep Learning a short sample of music showed better results than the previous model and the model with Softmax layer added to the model performed best. The need for the explosive growth of digital media and the automatic classification of music genres in numerous streaming services is increasing. Future research will need to reduce the proportion of undifferentiated songs and develop algorithms for the last category classification of undivided songs.