• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.652-655
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• 2021

Among various inter prediction techniques of Versatile Video Coding (VVC), adaptive motion vector resolution (AMVR) technology has been adopted. However, for AMVR, various MVs should be tested per each coding unit, which needs a computation of rate-distortion cost and results in an increase in encoding complexity. Therefore, in order to reduce the encoding complexity of AMVR, it is necessary to effectively find an optimal AMVR mode. In this paper, we propose a lightweight neural network-based AMVR decision algorithm based on more diverse datasets.

• ETRI Journal
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• v.29 no.3
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• pp.390-392
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• 2007

In this paper, we propose a new error concealment (EC) method using inter-layer correlation for scalable video coding. In the proposed method, the auxiliary motion vector (MV) and the auxiliary mode number (MN) of intra prediction are interleaved into the bitstream to recover the corrupted frame. In order to reduce the bit rate, the proposed method encodes the difference between the original and the predicted values of the MV and MN instead of the original values. Experimental results show that the proposed EC outperforms the conventional EC by 2.8 dB to 6.7 dB.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.208-220
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• 2021

This paper evaluates the performance of multilayer VVC and SHVC. Multilayer VVC supports a multi-layer coding and many coding technologies have been added and extended compared to SHVC. For this reason, it is necessary to evaluate the multi-layer coding performance of VVC and the coding performance for inter-layer reference prediction. Multilayer VVC provides significant BD-rate improvement of AI 24.4%, RA 29.4%, LDB 29.4%, LDP 32.6% on average when compared to SHVC, so that it is shown that VVC can provide scalability more efficiently. On the other hand, the complexity of the encoding time increases by an average of 14 times and decoding time by an average of 1.8 times, which requires efforts to reduce the complexity.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1093-1101
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• 2012

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding exploits inter-view correlations among pictures of neighboring views and temporal correlations among pictures of the same view. Multi-view video coding which uses many cameras requires a method to reduce the computational complexity. In this paper, we proposed an efficient prediction structure to improve performance of multi-view video coding. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several small groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experimental results show that the proposed prediction structure shows good performance in image quality and bit-rates. When compared to the performance of hierarchical B pictures of Fraunhofer-HHI, the proposed prediction structure achieved 0.07~0.13 (dB) of PSNR gain and was down by 6.5(Kbps) in bitrate.

• Environmental Engineering Research
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• v.11 no.4
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• pp.201-207
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• 2006

A simple empirical model with good quantitative prediction of inter-particle and intra-particle distance in a cake layer with respect to ionic strength was developed. The model is an inverse length scale with functions of interaction energy and hydrodynamic factor and it explains that the inter-particle and intra-particle distance in a cake is directly related to the effective size of particles. Particle compressibility with respect to ionic strength was also predicted by the model. The model corroborated very well with experimental results of polystyrene microsphere latex particles microfiltation in a dead end operation. From the results of the model, specific cake resistance could be controlled by the same variables affecting the height of particle energy barrier described by the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.156-161
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• 2003

It is an interest problem to predict substance distributions in three-dimensional space. Recently, a research field as Geostatistics is advanced. It is a kind of inter- or extrapolation mathematically. Some useful means for the inter- and extrapolation are known, in which slide window method with neural networks is hopeful one. We propose multi-dimensional extrapolation using multi-layer neural networks and the slide-window method. The multi-dimensional extrapolation is not similar to one-dimension. It has plural algorithms. We researched line predictors and local-plain predictors I two-dimensional space. The both predictors are equivalent; however, in multi-dimensional extrapolation, it is very important to find the direction of predictions. Especially, since the slide window method requires information to predict the future in sampling data, if they are not ordered appropriately in the direction, the predictor cannot operate. We tested the extrapolation for typical two-dimensional functions, and found an excellent character of slide-window method based on local-plain. By using the method, we can extrapolate the function until twice-outer regions of the definitions.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.108-121
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• 2012

As Scalable Video Coding (SVC) is a video compression standard extended from H.264/AVC, it is a way to provide scalability in terms of temporal, spatial and quality. Although the compression efficiency of SVC is increased due to the scalability in many aspect, it is essential to reduce the complexity in order to efficiently use because the complexity is relatively increased. To reduce the complexity of SVC in the paper, we propose fast mode decision algorithm to reduce the complexity of encoding process using direction information of B-picture by efficiently performing inter-layer prediction. The proposed algorithm is a fast mode decision algorithm that makes different from detection mode number of forward and backward, bi-direction in the way using best mode of base-layer up-sampled after simply SKIP mode detection using the direction information of best mode of base-layer up-sampled. The experimental results show that the proposed algorithm approach can achieve the maximum computational time saving about 53% with almost no loss of rate distortion (RD) performance in the enhancement layer.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.765-780
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• 2012

In this paper, we propose a fast mode decision method that determines the coding unit depth for enhancement layers to improve an encoding speed of a scalable video encoder based on HEVC. To decide the coding unit depth of the enhancement layer, firstly, the coding unit depth of the corresponded coding unit in the basement layer is employed. At this stage, the final CU depth is decided by calculating the rate-distortion costs of one lower depth to one upper depth of the referenced depth. The proposed method can reduce a computational load since it does not calculate the rate-distortion costs for all the depths of a target CU. We found that the proposed algorithm decreases encoding complexity of 26% with approximately 1.4% bit increment, compared with the simulcast encoder of the HM 4.0.

• Macromolecular Research
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• v.17 no.10
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• pp.797-806
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• 2009

The mechanical and thermal behaviors of polyamide-6/clay nanocomposites were studied using the continuum-based, micromechanical models such as Mori-Tanaka, Halpin-Tsai and shear lag. Mechanic-based model prediction provides a better understanding regarding the dependence of the nanocomposites' reinforcement efficiency on conventional filler structural parameters such as filler aspect ratio ($\alpha$), filler orientation (S), filler weight fraction (${\Psi}_f$), and filler/matrix stiffness ratio ($E_f/E_m$). For an intercalated and exfoliated nanocomposite, an effective, filler-based, micromechanical model that includes effective filler structural parameters, the number of platelets per stack (n) and the silicate inter-layer spacing ($d_{001}$), is proposed to describe the mesoscopic intercalated filler and the nanoscopic exfoliated filler. The proposed model nicely captures the experimental modulus behaviors for both intercalated and exfoliated nanocomposites. In addition, the model prediction of the heat distortion temperature is examined for nanocomposites with different filler aspect ratio. The predicted heat distortion temperature appears to be reasonable compared to the heat distortion temperature obtained by experimental tests. Based on both the experimental results and model prediction, the reinforcement efficiency and heat resistance of the polyamide-6/clay nanocomposites definitely depend on both conventional (${\alpha},\;S,\;{\Psi}_f,\;E_f/E_m$) and effective (n, $d_{001}$) filler structural parameters.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.405-408
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• 2017

Based on the fact that high similarities exist between viewpoints of multi-view images, MV-HEVC achieves high encoding efficiency by performing conventional temporal direction prediction in a single viewpoint as well as inter-view prediction between viewpoints. In this paper, we propose to integrate SHVC and MVC (Multi-view Video Coding) to implement scalable multi-view video encoder using HEVC as a base layer. According to experimental results, it is verified that the BD-PSNR improvement reaches up to 1.5dB while reducing the BD-Bitrate by around 50~60%.